File size: 56,990 Bytes
6fa4bc9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 |
{
"paper_id": "R11-1010",
"header": {
"generated_with": "S2ORC 1.0.0",
"date_generated": "2023-01-19T15:05:02.185064Z"
},
"title": "An Open Source Punjabi Resource Grammar",
"authors": [
{
"first": "Shafqat",
"middle": [
"Mumtaz"
],
"last": "Virk",
"suffix": "",
"affiliation": {
"laboratory": "",
"institution": "University of Gothenburg",
"location": {
"country": "Sweden"
}
},
"email": "virk@chalmers.se"
},
{
"first": "Muhammad",
"middle": [],
"last": "Humayoun",
"suffix": "",
"affiliation": {
"laboratory": "",
"institution": "University of Savoie",
"location": {
"country": "France"
}
},
"email": "humayoun@gmail.com"
},
{
"first": "Aarne",
"middle": [],
"last": "Ranta",
"suffix": "",
"affiliation": {
"laboratory": "",
"institution": "University of Gothenburg",
"location": {
"country": "Sweden"
}
},
"email": ""
}
],
"year": "",
"venue": null,
"identifiers": {},
"abstract": "We describe an open source computational grammar for Punjabi; a resource-poor language. The grammar is developed in GF (Grammatical framework), which is a tool for multilingual grammar formalism. First, we explore different syntactic features of Punjabi and then we implement them in accordance with GF grammar requirements, to make Punjabi the 17th language in the GF resource grammar library.",
"pdf_parse": {
"paper_id": "R11-1010",
"_pdf_hash": "",
"abstract": [
{
"text": "We describe an open source computational grammar for Punjabi; a resource-poor language. The grammar is developed in GF (Grammatical framework), which is a tool for multilingual grammar formalism. First, we explore different syntactic features of Punjabi and then we implement them in accordance with GF grammar requirements, to make Punjabi the 17th language in the GF resource grammar library.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Abstract",
"sec_num": null
}
],
"body_text": [
{
"text": "Grammatical Framework (Ranta, 2004 ) is a special-purpose programming language for multilingual grammar applications. It can be used to write multilingual resource or application grammars (two types of grammars in GF).",
"cite_spans": [
{
"start": 22,
"end": 34,
"text": "(Ranta, 2004",
"ref_id": "BIBREF4"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Introduction",
"sec_num": "1."
},
{
"text": "Multilingualism of the GF grammars is based on the principle that same grammatical categories (e.g. noun phrases and verb phrases) and syntax rules (e.g. predication) can appear in different languages (Ranta, 2009a) . A collection of all such categories and rules, which are independent of any language, makes the abstract syntax of GF grammars (every GF grammar has two levels: abstract and concrete). More precisely, the abstract syntax defines semantic conditions to form abstract syntax trees. For example the rule that a common noun can be modified by an adjective is independent of any language and hence is defined in the abstract syntax, e.g.: However, the way this rule is implemented may vary from one language to another; as each language may have different word order and/or agreement rules. For this purpose, we have the concrete syntax, which is a set of linguistic objects (strings, inflection tables, records) providing rendering and parsing. We may have multiple parallel concrete syntaxes for one abstract syntax, which makes the GF grammars multilingual. Also, as each concrete syntax is independent from others, it becomes possible to model the rules accordingly (i.e. word order, word forms and agreement features are chosen according to language requirements).",
"cite_spans": [
{
"start": 201,
"end": 215,
"text": "(Ranta, 2009a)",
"ref_id": "BIBREF5"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Introduction",
"sec_num": "1."
},
{
"text": "Current state-of-the-art machine translation systems such as Systran, Google Translate, etc. provide huge coverage but sacrifice precision and accuracy of translations. On the contrary, domain-specific or controlled multilingual grammar based translation systems can provide a higher translation quality, on the expense of limited coverage. In GF, such controlled grammars are called application grammars.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Introduction",
"sec_num": "1."
},
{
"text": "Writing application grammars from scratch can be very expensive in terms of time, effort, expertise and money. GF provides a library called the GF resource library that can ease this task. It is a collection of linguistic oriented but general-purpose resource grammars, which try to cover the general aspects of different languages (Ranta, 2009a) .",
"cite_spans": [
{
"start": 332,
"end": 346,
"text": "(Ranta, 2009a)",
"ref_id": "BIBREF5"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Introduction",
"sec_num": "1."
},
{
"text": "Instead of writing application grammars from scratch for different domains, one may use resource grammars as libraries (Ranta, 2009b) 2 . This method enables to create the application grammar much faster with a very limited linguistic knowledge.",
"cite_spans": [
{
"start": 119,
"end": 133,
"text": "(Ranta, 2009b)",
"ref_id": "BIBREF6"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Introduction",
"sec_num": "1."
},
{
"text": "The number of languages covered by GF resource library is growing (17 including Punjabi). Previously, GF and/or its libraries have been used to develop a number of multilingual as well as monolingual domain-specific application grammars (see GF homepage 3 for details on these application grammars).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Introduction",
"sec_num": "1."
},
{
"text": "In this paper, we describe the resource grammar development for Punjabi. Punjabi is an Indo-Aryan language widely spoken in Punjab regions of Pakistan and India. Punjabi is among one of the morphologically rich languages (others include Urdu, Hindi, Finish, etc) with SOV word order, partial ergative behavior, and verb compounding. In Pakistan it is written in Shahmukhi, and in India, it is written in Gurmukhi script (Humayoun, 2010) . Language resources for Punjabi are very limited (especially for the one spoken in Pakistan). With the best of our knowledge this work is the first attempt of implementing a computational Punjabi grammar as open-source software, covering a fair enough part of Punjabi morphology and syntax.",
"cite_spans": [
{
"start": 420,
"end": 436,
"text": "(Humayoun, 2010)",
"ref_id": "BIBREF2"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Introduction",
"sec_num": "1."
},
{
"text": "Every grammar in GF resource grammar library has a test lexicon, which is built through the lexical functions called the lexical paradigms; see (Bringert et el, 2011) for synopsis. These paradigms take lemma of a word and make finite inflection tables, containing different forms of the word, according to the lexical rules of that particular language. A suite of Punjabi resources including morphology and a big lexicon are reported by (Humayoun and Ranta, 2010) . With minor required adjustments, we have reused morphology and a subset of that lexicon, as a test lexicon of about 450 words for our grammar implementation. However, the morphological details are beyond the scope of this paper and we refer to (Humayoun and Ranta, 2010) for more details on Punjabi morphology.",
"cite_spans": [
{
"start": 144,
"end": 166,
"text": "(Bringert et el, 2011)",
"ref_id": null
},
{
"start": 437,
"end": 463,
"text": "(Humayoun and Ranta, 2010)",
"ref_id": "BIBREF2"
},
{
"start": 710,
"end": 736,
"text": "(Humayoun and Ranta, 2010)",
"ref_id": "BIBREF2"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Morphology",
"sec_num": "2."
},
{
"text": "While morphology is about types and formation of individual words (lexical categories), it is the syntax, which decides how these words are grouped together to make well-formed sentences. For this purpose, individual words, which belong to different lexical categories, are converted into richer syntactic categories, i.e. noun phrases (NP), verb phrases (VP), and adjectival phrases (AP), etc. With this up-cast the linguistic features such as word-forms, number & gender information, and agreements, etc, travel from individual words to the richer categories.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Syntax",
"sec_num": "3."
},
{
"text": "In this section, we explain this conversion from lexical to syntactic categories and afterwards, we demonstrate how to glue the individual pieces to make clauses. These are then can be used to make well-formed sentences in Punjabi. The following subsections explain various types of phrases.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Syntax",
"sec_num": "3."
},
{
"text": "A noun phrase (NP) is a single word or a group of words that does not have a subject and a predicate of its own, and does the work of a noun (Verma, 1974) . Now we show the structure of noun phrase in our implementation, followed by the description of its different parts. The label 's' is an inflection table from NPCase to string (NPCase => Str). NPCase has two constructs (NPC Case, and NPErg) as shown below:",
"cite_spans": [
{
"start": 141,
"end": 154,
"text": "(Verma, 1974)",
"ref_id": "BIBREF7"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "NPCase = NPC Case | NPErg ; Case = Dir | Obl | Voc | Abl ;",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "The construct (NPC Case) stores the lexical cases (i.e. Direct, Oblique, Vocative and Ablative) of a noun 4 . As an example consider the following table for the noun \"boy\":",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "s .NPC Dir => m \u028a n \u0256 \u0251 : \u010c \u0133 s .NPC Obl => m \u028a n \u0256 \u025b \u010d \u0133 s .NPC Voc => m \u028a n \u0256 i : a \u0115 \u0133 s .NPC Abl => m \u028a n \u0256 \u025b o : \u0273 \u0133",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "Other than storing the lexical cases of a noun as shown in the above table, we also construct the ergative case (i.e. NPErg in the code above). We do it at the noun phrase level for the 4 Punjabi nouns have four lexical cases.",
"cite_spans": [
{
"start": 186,
"end": 187,
"text": "4",
"ref_id": null
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "following reason: In Urdu, the case markers that follow the nouns in the form of post-positions cannot be handled at lexical level through morphological suffixes and thus need to be handled at syntax level (Butt and King, 2002) 5 . It also applies to Punjabi. So we construct the ergative case of a noun by attaching ergative case marker 'n\u025b' to the oblique case of the noun at NP level. For instance, the ergative form of our running example \"boy\" is:",
"cite_spans": [
{
"start": 206,
"end": 227,
"text": "(Butt and King, 2002)",
"ref_id": "BIBREF1"
},
{
"start": 228,
"end": 229,
"text": "5",
"ref_id": null
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "s.NPErg => m \u028a n \u0256 \u025b n \u025b _Erg \u010d \u0133 a",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "It is used for the subjects of perfective transitive verbs (see Section 3.5 for more details).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "The label 'a' represents the agreement feature (Agr) and stores information about gender, number and person that will be used for agreement with other constituents. It is defined as follows:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "Agr = Ag Gender Number Person ;",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "In Punjabi, the gender can be masculine or feminine; number can be singular and plural; and person can be first, second casual, second with respect and third person near & far. These are defined as shown below:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "Gender = Masc | Fem ; Number = Sg | Pl ; Person = Pers1 | Pers2_Casual | Pers2_Respect | Pers3_Near | Pers3_Far",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "Finally, the label 'isPron' is a Boolean parameter, which shows whether NP is constructed from a pronoun. This information is important when dealing with the exceptions in ergative behavior of verbs for the first and second person pronouns in Punjabi. For example consider the following constructions: From the above examples, we can see that, when we have the first or second person pronoun as subject, the ergative case marker is not used (first two examples). On the contrary, it is used in all other cases. So for our running example, i.e. the noun (boy, m\u028an\u0256\u0251:), the label 'isPron' is false. Construction: First, the lexical category noun (N) is converted to an intermediate category, common noun (CN) through the UseN function. CN is a syntactic category, which is used to deal with the modifications of nouns by adjectives, determiners, etc. Then, the common noun is converted to the syntactic category, noun phrase (NP). Three main types of noun phrases are: (1) common nouns with determiners, (2) proper names, and 3pronouns. We build these noun phrases through different noun phrase construction functions depending on the constituents of NP. As an example consider (1). We define it with a function DetCN given below: Here (Det) is a lexical category representing determiners. The above given function takes the determiner (Det) and the common noun (CN) as parameters and builds the NP, by combining appropriate forms of the determiner and the common noun agreeing with each other. For example if 'every' and 'boy' are the parameters for the above given function the result will be a NP: every boy, h \u0259 r m \u028a n \u0256 \u0251 :",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "m i : \u0273 _ I",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "Every boy,",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": ". Consider the linearization of DetCN:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "lin DetCN det cn = { s=\\\\c => detcn2NP det cn c det.n; a = agrP3 cn.gdet.n ; isPron = False } ;",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "As we know from the structure of NP (given in the beginning of \u00a73.1) 's' represents the inflection table used to store different forms of NP built by the following line from the above code:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "s = \\\\c => detcn2NP det cn c det.n;",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "Notice that the operator ('\\\\') is used as shorthand to represent different rows of the inflection table 's'. An alternative but a verbose code segment for the above line will be: Also notice that the selection operator (the exclamation sign !) is used to select appropriate forms from the inflection tables (i.e. cn.s!n!c, which means the form of the common noun with number 'n' and case 'c' from the inflection table cn.s).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "s =",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "Other main types of noun phrases (2) and (3) are constructed through the following functions. This covers only three main types of noun phrases, but there are other types of noun phrases as well, i.e. adverbial post-modified NP, adjectival modified common nouns etc. In order to cover them we have one function for each such construction. Few of these are given below; for full details we refer to (Bringert et el, 2011) . The structure of VPHForm makes sure that we preserve all inflectional forms of the verb. In it we have three cases: (1) Inflectional forms inflecting for tense (VPPTense) and number, gender, person with Agr defined on page 3. 2The second constructor (VPInf) carries the infinitive form. (3) On the contrary, VPStem carries the root form. The reason for separating these three cases is that they cannot occur at the same time.",
"cite_spans": [
{
"start": 398,
"end": 420,
"text": "(Bringert et el, 2011)",
"ref_id": null
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "The label 'inf' stores the required form of the verb in that corresponding tense, whereas 'fin' stores the copula (auxiliary verb).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "The label 'obj' on the other hand, stores the object of the verb and also the agreement information of the object. The label 'subj' stores information about transitivity of the verb with VType, which include: intransitive, transitive or di-transitive:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "VType = VIntrans|VTrans|VDiTrans ;",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "The label 'comp' stores the complement of the verb. Notice that it also inflects in number, gender and person (with Agr defined on page 3), whereas the label 'ad' stores the adverb.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "Finally, 'embComp' stores the embedded complement. It is used to deal with exceptions in the word order of Punjabi when making a clause. For instance, if a sentence or a question sentence is a complement of the verb then it takes a different position in the clause; i.e. it comes at very end of the clause as shown in the example with bold-face: On the contrary, if an adverb is used as a complement of verb then it comes before the main verb, as shown in the following example: The lexical category V has three forms (corresponding to perfective/imperfective aspects and subjunctive mood). These forms are then used to make four forms (VPPres, VPPast, VPFutr, VPPerf in the above code) at the VP level, which are used to cover different combinations of tense, aspect and mood of Punjabi at clause level.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "oo",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "oo",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "As an example, consider the explanation of the above code in bold-face. It builds a part of the inflection table represented by 's' for VPPres and all possible combination of gender, number and person (Ag g n p). As shown above, the imperfective form of lexical category V (VF Imperf p n g) is used to make present tense at VP-level. The main verb is stored in the field labeled as 'inf' and the corresponding auxiliary verb (copula) is stored in the label 'fin'.",
"cite_spans": [
{
"start": 324,
"end": 333,
"text": "VP-level.",
"ref_id": null
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "All other parts of VP are initialized to default or empty values in the above code. These parts will be used to enrich the VP with other constituents, e.g. adverb, complement etc. This is done in other VP construction functions including but not limited to: ",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "Want",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Noun Phrases",
"sec_num": "3.1."
},
{
"text": "At morphological level, Punjabi adjectives inflect in number, gender and case (Humayoun and Ranta, 2010) . At syntax level, they agree with the noun they modify using the agreement information of the NP. Adjectival phrase (AP) can be constructed simply from the lexical category adjective (A) through the following function:",
"cite_spans": [
{
"start": 78,
"end": 104,
"text": "(Humayoun and Ranta, 2010)",
"ref_id": "BIBREF2"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Adjectival Phrases",
"sec_num": "3.3."
},
{
"text": "PositA : A \u2192 AP ; (Warm, g \u0259 r \u0259 m )",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Adjectival Phrases",
"sec_num": "3.3."
},
{
"text": "Or from other categories such as: ",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Adjectival Phrases",
"sec_num": "3.3."
},
{
"text": "Warmer than I, m i \u02d0 r e \u02d0 _ I",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Adjectival Phrases",
"sec_num": "3.3."
},
{
"text": "The construction of Punjabi adverbs is very simple because \"they are normally unmarked and don't inflect\" (Humayoun and Ranta, 2010) . We have different construction functions for Adverbs and other closed classes both at lexical and syntactical level. For instance, consider the construction of adverbs with two functions (but not limited to):",
"cite_spans": [
{
"start": 106,
"end": 132,
"text": "(Humayoun and Ranta, 2010)",
"ref_id": "BIBREF2"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Adverbs and Closed Classes",
"sec_num": "3.4."
},
{
"text": "Warmly, g \u0259 r \u0259 m d \u0292 \u028b x i \u02d0 fun PositAdvAdj : A \u2192 Adv ; Very quickly, b o h t _ v e r y t i \u02d0 z i _ q u i c k l y d e n a l _ c o u p l a fun AdAdv : AdA \u2192 Adv \u2192 Adv ;",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Adverbs and Closed Classes",
"sec_num": "3.4."
},
{
"text": "While a phrase is a single word or group of words, which are grammatically linked to each other, a clause on the other hand, is a single phrase or group of phrases.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Clauses",
"sec_num": "3.5."
},
{
"text": "Different types of phrases (e.g. NP, VP, etc) are grouped together to make clauses 6 . Clauses are then used to make sentences. In GF tense system the difference between a clause and a sentence is: A clause has a variable tense while a sentence has a fixed tense.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Clauses",
"sec_num": "3.5."
},
{
"text": "We first construct clauses and then just fix their tense in order to make sentences. The most important construction of a clause is:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Clauses",
"sec_num": "3.5."
},
{
"text": "PredVP : NP \u2192 VP \u2192 Cl; --Ali walks",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Clauses",
"sec_num": "3.5."
},
{
"text": "The clause (Cl) has the following type: The tense system of GF resource library covers only eight combinations with four tenses (present, past, future and conditional) and two anteriorities (Anter and Simul). It does not cover the full tense system of Punjabi, which is structured around the aspect and the tense/mood. We make sentences in twelve different tenses (VPHTense in the above given code) at clause level to get a maximum coverage of the Punjabi tense system. Polarity is used to construct positive and negative, while Order is used to construct direct and question clauses.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Clauses",
"sec_num": "3.5."
},
{
"text": "We ensure the SOV agreement by saving all needed features in NP. These are made accessible in the PredVP function.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Clauses",
"sec_num": "3.5."
},
{
"text": "A distinguishing feature of Punjabi SOV agreement is ergative behavior where transitive perfective verb may agree with the direct object instead of the subject. Ergativity is ensured by selecting the agreement features and noun-form accordingly. We demonstrate this in the following simplified code segment: subj agr : NPCase * Agr = case vt of { 6 Verb phrases alone can also be used as clause some times. For perfective aspect (VPImpPast), if the verb is transitive then it agrees with the object and therefore the ergative case of NP is used (VTrans in the above code).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Clauses",
"sec_num": "3.5."
},
{
"text": "For DiTransitive (i.e. VDiTrans in the above code) the agreement is set to default but the ergative case is still needed.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Clauses",
"sec_num": "3.5."
},
{
"text": "In all other cases, specified with the wild card \"_\" above, the agreement is made with the subject (np.a), and we use the direct case (i.e.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Clauses",
"sec_num": "3.5."
},
{
"text": "After selecting the appropriate forms of each constituent (according to the agreement features) they are grouped together to form the clause. For instance, consider the following simplified code segment combining different constituents of a Where:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "NPC Dir).",
"sec_num": null
},
{
"text": "(1) np.s!subj is the subject;",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "NPC Dir).",
"sec_num": null
},
{
"text": "(2) vp.obj.s is the object (if any); (3) vp.ad is the adverb (if any); (4) vp.comp!np.a is verb's complement; (5) nahim is the negative clause constant; (6) vps.inf is the verb; (7) vps.fin is the auxiliary verb; (8) vp.embComp is an embedded complement.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "NPC Dir).",
"sec_num": null
},
{
"text": "The grammar we have developed consists of 40 categories and 190 syntax functions. It covers only a fair enough part of the language. The reason for this limitation is approach of the common abstract syntax defined for all the languages in the GF resource library. Indeed it is not possible to have an abstract syntax, which is common to, and covers all features of all languages. Consequently, the current grammar does not cover all aspects of Punjabi.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coverage and Limitations",
"sec_num": "4."
},
{
"text": "However, this does not put any limitation on the extension of a language resource. It can be extended by implementing language specific features as extra language-specific modules. However these features will not be accessible through the common API, but can be accessed in the Punjabi application grammars.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Coverage and Limitations",
"sec_num": "4."
},
{
"text": "It is important to note that completeness is not the success criteria for this kind of grammar based resource but accuracy is (Ranta 2009b) . Evaluating a resource grammar is just like evaluating a software library in general. However, this type of evaluation is different from evaluation of a natural language processing application in general, where testing is normally done against some corpus. To evaluate the accuracy, we use the Punjabi resource grammar to translate, and observe, a test suite of examples 7 from English to Punjabi and vice versa. We achieved an accuracy of 98.1%. The reason for not having 100% accuracy is that our current grammar does not cover all aspects of the language. One such aspect is compound verbs of Punjabi, formed by nouns and the auxiliary verb 'to be' (hona:). In this case, its gender must agree with the inherent gender of the noun. We have not yet covered this agreement for compound verbs and therefore, produce incorrect translations. An interesting (yet wrong) example would be: , the boy slept weeping). Coverage of such language specific details is one direction for the future work.",
"cite_spans": [
{
"start": 126,
"end": 139,
"text": "(Ranta 2009b)",
"ref_id": "BIBREF6"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Evaluation and Future Work",
"sec_num": "5."
},
{
"text": "In general language resources for Punjabi are very limited; especially for the one spoken in Pakistan and written in Shahmukhi. Furthermore, most of the applications related to Punjabi are designed only for the Punjabi, written and spoken in India; hence, only support the Gurmukhi script. A review of such applications is given in (Lehal, 2009) .",
"cite_spans": [
{
"start": 332,
"end": 345,
"text": "(Lehal, 2009)",
"ref_id": "BIBREF3"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Related Work and Conclusion",
"sec_num": "6."
},
{
"text": "There are some attempts to interchange between these scripts with transliteration 7 See (Bringert et el, 2011) for this test suite of examples. systems. However, the current systems only seem to provide partial solutions, mainly because of the vocabulary differences (Humayoun and Ranta, 2010) .",
"cite_spans": [
{
"start": 88,
"end": 110,
"text": "(Bringert et el, 2011)",
"ref_id": null
},
{
"start": 267,
"end": 293,
"text": "(Humayoun and Ranta, 2010)",
"ref_id": "BIBREF2"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Related Work and Conclusion",
"sec_num": "6."
},
{
"text": "A transfer-based machine translation system reported in (Lehal, 2009) translates between Punjabi and Hindi only. On the contrary, the Punjabi resource grammar is based on Interlingua approach, which makes it possible to translate between seventeen languages in parallel. With the best of our knowledge this work is the first attempt to implement a computational Punjabi grammar as open source.",
"cite_spans": [
{
"start": 56,
"end": 69,
"text": "(Lehal, 2009)",
"ref_id": "BIBREF3"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Related Work and Conclusion",
"sec_num": "6."
},
{
"text": "We have described the implementation of the computational grammar for Punjabi. It might be a useful resource, and may encourage other researchers to work in this direction.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Related Work and Conclusion",
"sec_num": "6."
},
{
"text": "As the resource grammar does not cover full features of Punjabi, although it is not possible to use it for parsing and translation of arbitrary text, it is best suited for building domain specific application grammars.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Related Work and Conclusion",
"sec_num": "6."
},
{
"text": "In GF code, cat and fun belong to abstract syntax. On the contrary, lincat and lin belong to concrete syntax.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "This idea is influenced by programming language API tradition in which, a standard general-purpose library is supported by the language. It is then used by programmers to write specific applications.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "http://www.grammaticalframework.org/",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "This also explains the reason for NPErg to be separate from \"NPC Case\".",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
}
],
"back_matter": [],
"bib_entries": {
"BIBREF0": {
"ref_id": "b0",
"title": "GF Resource Grammar Library Synopsis",
"authors": [
{
"first": "B",
"middle": [],
"last": "Bringert",
"suffix": ""
},
{
"first": "T",
"middle": [],
"last": "Hallgren",
"suffix": ""
},
{
"first": "A",
"middle": [],
"last": "Ranta",
"suffix": ""
}
],
"year": 2011,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "B. Bringert, T. Hallgren, A. Ranta. 2011. GF Resource Grammar Library Synopsis.",
"links": null
},
"BIBREF1": {
"ref_id": "b1",
"title": "The Parallel Grammar Project",
"authors": [
{
"first": "M",
"middle": [],
"last": "Butt",
"suffix": ""
},
{
"first": "H",
"middle": [],
"last": "Dyvik",
"suffix": ""
},
{
"first": "T",
"middle": [
"H"
],
"last": "King",
"suffix": ""
},
{
"first": "H",
"middle": [],
"last": "Masuichi",
"suffix": ""
},
{
"first": "C",
"middle": [],
"last": "Rohrer",
"suffix": ""
}
],
"year": 2002,
"venue": "Proceedings of COLING-2002. Workshop on Grammar Engineering and Evaluation",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "M. Butt, H. Dyvik, T. H. King, H. Masuichi, C. Rohrer. 2002. The Parallel Grammar Project. In Proceedings of COLING-2002. Workshop on Grammar Engineering and Evaluation.",
"links": null
},
"BIBREF2": {
"ref_id": "b2",
"title": "Developing Punjabi Morphology, Corpus and Lexicon",
"authors": [
{
"first": "M",
"middle": [],
"last": "Humayoun",
"suffix": ""
},
{
"first": "A",
"middle": [],
"last": "Ranta",
"suffix": ""
}
],
"year": 2010,
"venue": "The 24th Pacific Asia conference on Language, Information and Computation",
"volume": "",
"issue": "",
"pages": "163--172",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "M. Humayoun and A. Ranta. 2010. Developing Punjabi Morphology, Corpus and Lexicon. The 24th Pacific Asia conference on Language, Information and Computation. pp: 163-172.",
"links": null
},
"BIBREF3": {
"ref_id": "b3",
"title": "A Survey of the State of the Art in Punjabi Language Processing",
"authors": [
{
"first": "G",
"middle": [
"S"
],
"last": "",
"suffix": ""
}
],
"year": 2009,
"venue": "Language In India",
"volume": "9",
"issue": "10",
"pages": "9--23",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "G. S. Lehal. 2009. A Survey of the State of the Art in Punjabi Language Processing, Language In India, Volume 9, No. 10, pp. 9-23.",
"links": null
},
"BIBREF4": {
"ref_id": "b4",
"title": "Grammatical Framework: A Type-Theoretical Grammar Formalism",
"authors": [
{
"first": "A",
"middle": [],
"last": "Ranta",
"suffix": ""
}
],
"year": 2004,
"venue": "Journal of Functional Programming",
"volume": "14",
"issue": "2",
"pages": "145--189",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "A. Ranta. 2004. Grammatical Framework: A Type- Theoretical Grammar Formalism. Journal of Functional Programming, 14(2), pp. 145-189.",
"links": null
},
"BIBREF5": {
"ref_id": "b5",
"title": "Grammatical Framework: A Multilingual Grammar Formalism",
"authors": [
{
"first": "A",
"middle": [],
"last": "Ranta",
"suffix": ""
}
],
"year": 2009,
"venue": "Language and Linguistics Compass",
"volume": "3",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "A. Ranta. 2009a. Grammatical Framework: A Multilingual Grammar Formalism, Language and Linguistics Compass, Vol. 3.",
"links": null
},
"BIBREF6": {
"ref_id": "b6",
"title": "Grammars as Software Libraries",
"authors": [
{
"first": "A",
"middle": [],
"last": "Ranta",
"suffix": ""
}
],
"year": 2009,
"venue": "From Semantics to Computer Science",
"volume": "",
"issue": "",
"pages": "281--308",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "A. Ranta. 2009b. Grammars as Software Libraries. In Y. Bertot, G. Huet, J-J. L\u00e9vy, and G. Plotkin (eds.), From Semantics to Computer Science, Cambridge University Press, pp. 281-308.",
"links": null
},
"BIBREF7": {
"ref_id": "b7",
"title": "The Structure of the Noun Phrase in English and Hindi by Review author(s)",
"authors": [
{
"first": "M",
"middle": [
"K K"
],
"last": "Verma ; R",
"suffix": ""
},
{
"first": "L",
"middle": [
"A"
],
"last": "Barz",
"suffix": ""
}
],
"year": 1974,
"venue": "Schwarzschild Journal of the American Oriental Society",
"volume": "94",
"issue": "4",
"pages": "492--494",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "M. K. Verma. 1974. The Structure of the Noun Phrase in English and Hindi by Review author(s): R. K. Barz, L. A. Schwarzschild Journal of the American Oriental Society, Vol. 94, No. 4, pp. 492-494.",
"links": null
}
},
"ref_entries": {
"FIGREF1": {
"text": "In GF, we represent the NP as a record with three fields, labeled as: 's' , 'a' and",
"num": null,
"type_str": "figure",
"uris": null
},
"TABREF0": {
"type_str": "table",
"content": "<table><tr><td/><td/><td/><td/><td/><td/><td/><td/><td>m \u028a n \u0256 \u025b : _ \u0133 a \u010f b o y n \u025b : _ E r g M a r \u010d \u0112 \u0115 \u0144 a \u0151 \u014b</td><td>k e r</td><td>r u : \u0288 i</td><td>: _ b r</td><td>e a d</td><td>k \u02b0 a d i</td><td>_ a t :</td><td>e</td></tr><tr><td/><td colspan=\"3\">r o</td><td colspan=\"3\">: \u0288 i : _ b r</td><td colspan=\"2\">e a d</td><td>k \u02b0</td><td>a d i : _ a t</td><td>e</td></tr><tr><td colspan=\"9\">\u010f I ate bread. \u0112 \u0115 \u0144 a \u0151 \u014b a \u0133</td></tr><tr><td>t u : \u0273 _</td><td>y o</td><td>u</td><td colspan=\"3\">r u : \u0288</td><td colspan=\"2\">i : _</td><td>b r e a d</td><td>k \u02b0 a d \u032a i : _ a</td><td>t e</td></tr><tr><td colspan=\"9\">\u010f You ate bread. \u0112 \u0115 \u0144 a \u0151 \u014b a</td></tr><tr><td colspan=\"5\">a u : n \u025b : _ H e</td><td colspan=\"4\">r u : \u0288 i : _ b r e</td><td>a d</td><td>k \u02b0 a d i : _ a t e</td></tr><tr><td colspan=\"9\">\u0151 He ate bread. \u010c \u010f \u0112 \u0115 \u0144 a \u0151 \u014b</td></tr></table>",
"num": null,
"text": "The boy ate bread.",
"html": null
},
"TABREF3": {
"type_str": "table",
"content": "<table><tr><td>VPH : Type = {</td></tr><tr><td>s:VPHForm => {fin, inf : Str};</td></tr><tr><td>obj : {s : Str ; a : Agr} ;</td></tr><tr><td>subj: VType ;</td></tr><tr><td>comp: Agr =>Str;</td></tr><tr><td>ad : Str ;</td></tr><tr><td>embComp : Str} ;</td></tr><tr><td>VPHForm =</td></tr><tr><td>VPTense VPPTense Agr|VPInf|VPStem ;</td></tr><tr><td>VPPTense=</td></tr><tr><td>PPres|VPPast|VPFutr|VPPerf;</td></tr><tr><td>Paris today, fun AdvNP : NP a j _ t \u2192 o d a y Adv p i \u02d0 r \u0259 s _ \u2192 P a r i s NP ;</td></tr><tr><td>Big house, fun AdjCN : AP \u028b \u0259 d d \u0251 \u02d0 \u2192 _ b i g CN \u0261 \u02b1 \u0259 r _ h \u2192 o u s e CN ;</td></tr><tr><td>3.2. Verb Phrases</td></tr><tr><td>A verb phrase (VP), as a syntactic category, is</td></tr><tr><td>the most complex structure in our constructions.</td></tr><tr><td>It carries the main verb and auxiliaries (such as</td></tr><tr><td>adverb, object of the verb, type of the verb,</td></tr><tr><td>agreement information, etc), which are then</td></tr><tr><td>used in the construction of other categories</td></tr><tr><td>and/or clauses.</td></tr><tr><td>Structure: In GF, we represent a verb phrase as</td></tr><tr><td>a record, as shown below:</td></tr></table>",
"num": null,
"text": "The label 's' represents an inflection table which keeps a record with two string values, i.e. {fin, inf : Str} for every value of VPHForm, which is defined as shown below:",
"html": null
},
"TABREF8": {
"type_str": "table",
"content": "<table/>",
"num": null,
"text": "Punjabi clause: np.s!subj ++ vp.obj.s ++ vp.ad ++ vp.comp!np.a ++ nahim ++ vps.inf ++ vps.fin ++ vp.embComp;",
"html": null
}
}
}
} |