Automated Extraction of Lexico-Syntactic Information
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1 Automated Extraction of Lexico-Syntactic Information Ondřej Bojar June 17, 2004
2 Outline 1 Motivation: Why syntactic lexicons? The two goals: Extending monolingual syntactic lexicons. Providing translation dictionaries with syntactic information. Summary and further research.
3 Syntactic Analysis: A Tough Cookie 2 Task: String of words tree. There are O(n n ) configurations theoretically possible. Ribarov 1 : sentences of 20 words have 300 structures in PDT, not 15.6 billion structures. Bojar [2004]: Allow observed local configurations and you ll get 9 n possible solutions. ( ) Statistical approaches simply cheat: they provide most common (frequent) analyses and therefore commonly seem to perform well. 1 Thesis in preparation
4 What a Lexicon Might Tell 3 (1) Manažeři The managers hypermarketu of the hypermarket přišli came na to trh the market. (2) Manažeři The managers hypermarketu the hypermarket přišli came The managers started to like the hypermarket. na to chuť taste.
5 The Two Goals 4 Extending monolingual syntactic lexicons. Current lexicons are incomplete. Building lexicons is a demanding task. Eventually, human decisions are necessary. An automatic preprocessing of corpus examples will help. Providing translation dictionaries with syntactic information. No formalized syntactic information in current dictionaries. Several semi-automatic steps proposed.
6 Extending Monolingual Syntactic Lexicons (I) 5 Treebank data are not sufficient: In PDT, after having observed 20,000 75,000 training sentences a new lemma (i.e. word) comes every test sentences a new full morphological tag comes every test sentences a new simplified tag 2 comes every test sentences PDT covers only 5,407 of 22,276 Czech verbs observed in Czech National Corpus. PDT contains more than 50 occurences per verb only for a few hundreds of verbs. 2 The simplified tag comprises only POS, SUBPOS, CASE, NUMBER and GENDER information.
7 Extending Monolingual Syntactic Lexicons (II) 6 Simple scheme: (Get more texts, e.g. from the Czech National Corpus or the Internet.) Morphologically annotate and disambiguate the sentences. Employ one of the parsers available for Czech to get the dependency trees. Extract the desired lexico-syntactic information. But current parsers are not accurate enough: (55% verb frames observed correctly) Select nice examples only. Keep sentences containing the observed phenomenon. Filter out all the sentences where the phenomenon is hidden and/or interferes with other phenomena.
8 Extending Monolingual Syntactic Lexicons (III) 7 Bojar [2002] designs a scripting language to select nice examples. A sample script to select nice examples of verbal frames helps current parsers: 5 10% improvement in correct dependencies. (Reached 88% dependencies correct) 10 15% improvement in correctly observed verb frames. (Reached 65% frames correct.) Different scripts should be used when extracting different kinds of data.
9 8 Providing Translation Dictionaries with Syntactic Information Accessible Czech-English dictionaries are for humans only. Necessary steps: Add morphological information. Add syntactic structure and agreement constraints. Provide entries with examples. Estimate monolingual and parallel frequencies. Benefits: Better machine translation, better monolingual syntactic lexicons. Possibility to align deep syntactic lexicons.
10 Steps Proposed 9 Manual disambiguation necessary. (We shall see.) Automatic morphological analysis and grouping saves a lot of work. Corpus data as an additional source: Data Annotation Level Possible Tasks to Augment Entries Entries Corpora no annotation any annotation no useful task morphology morphology possibly annotate internal agreement morphology trees find syntactic structure trees morphology find examples, estimate frequency trees trees confirm structure
11 Morphological Disambiguation: Manually! Noun and Noun/Adjective Correct Interpretation English Translation husa divoká Noun Adjective grey goose kniha účetní Noun Adjective account book napětí dovolené Noun Adjective permissible stress chyba měření Noun Noun measurement error plán prací Noun Noun schedule of operation rozsah měření Noun Noun range of measurement Numeral/Verb and Noun Correct Interpretation English Translation tři prdele Numeral Noun shitloads pět švestek Numeral Noun one s duds pět chválu Verb Noun sing someone s praises 10 These expressions allow for another interpretation, too, mostly kind of funny. Part of the idiom pick up one s duds.
12 Adding Syntactic Information 11 Manual annotation plausible and preferable for important groups. Noun Adjective Noun Syntactic Structure English Translation Komise Evropské unie náhrada způsobené škody látkou potažené sedadlo poruchy způsobené přijímačem nevolnost způsobená pohybem Once the syntactic information is present: Commission of the European Community dilapidation fabric-covered seat set noise kinesia Adding agreement constraints automatically, per structure. Searching for examples more precise. Searching allows to find more examples (modified multi-word entries).
13 Searching for Examples, Estimating Frequencies 12 In treebanks: Finding a subtree in a forest is easy. Only most prominent examples expected in PDT. Possibility to search in automatic trees of nice sentences. In plain corpora: Use agreement constraints to reject random collocations. Use syntactic structure to allow valid reordering and extra modifications present at specific places. Relevant source to estimate frequencies.
14 Aligning Deep Syntactic Lexicons 13 Czech and English deep syntactic lexicons under development. (VALLEX and FrameNet). Annotation schemata not equivalent but comparable. No common parallel corpus annotated with VALLEX on the Czech side and FrameNet on the English side. Use surface syntactic translation dictionary as a bridging link.
15 Conclusion and Further Research 14 We need syntactic lexicons. Automatic preprocessing saves effort (but does not solve the problem) for the two tasks: Extending monolingual syntactic lexicons. Providing translation dictionaries with syntactic information. Further goals: Build a syntactic Czech-English dictionary. Evaluate the utility of syntactic dictionaries.
16 15 References Ondřej Bojar. Automatická extrakce lexikálně-syntaktických údajů z korpusu (Automatic extraction of lexico-syntactic information from corpora). Master s thesis, ÚFAL, MFF UK, Prague, Czech Republic, In Czech. Ondřej Bojar. Czech Syntactic Analysis Constraint-Based, XDG: One Possible Start. Prague Bulletin of Mathematical Linguistics, 81:43 54, ISSN
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