CSA4040:Advanced Topics in NLP

1. CSA4040:Advanced Topics in NLP Information Extraction III Coreference CSA4050: Information Extraction III

2. References • D. Appelt & D. Israel, Introduction to IE Technology, IJCAI-99 Tutorial (1999) • Van Deemter and Kibble (1999) – What is coreference and what should coreference annotation be? • J.F. McCarthy & W. Lenhert, Using Decision Trees for Coreference Resolution, Proc. IJCAI 1995 CSA4050: Information Extraction III

3. What is Coreference? • The relation of coreference has been defined as holding between two noun phrases if they "refer to the same entity". • NPs α and β corefer if ref(α) = ref(β) • Equivalence relation: symmetrical, transitive and reflexive relation which partitions NPs into a set of equivalence classes. • Issue: must reference actually be identified in order to establish coreference? CSA4050: Information Extraction III

4. Different Kinds of Noun Phrase • Proper Nouns • Single Word • Multiple Word • Pronouns • Descriptions • Definite • Indefinite CSA4050: Information Extraction III

5. Coreference Tags in MUC6 • The ID and REF attributes are used to indicate that there is a coreference link between two strings. The ID is arbitrarily but uniquely assigned to the string during markup. The REF uses that ID to indicate the coreference link. <COREF ID="100">Lawson Mardon Group Ltd.</COREF> said <COREF ID="101" TYPE="IDENT" REF="100">it</COREF> ... CSA4050: Information Extraction III

6. Proper Nouns • Obvious case: two separate occurrences of the same proper noun.Paris is the capital of France; Paris is beautiful • or of identical phrasesMr. Dom Mintoff is as Mr. Dom Mintoff does • But note that similar tokens do not always co-refer, even when proper nouns. ExampleChris Attard met Chris Attard for the first time • Conversely, different looking tokens can coreferGenève; Geneva; Ginevra; Genf CSA4050: Information Extraction III

7. Amo et. al 1999 • Definition of “replicantes” relation between variants of Spanish proper names. Names are in replicancia relation if: • One of them coincides with the initials of the other. • The shorter is contained in the longer • Every word of the shorter is “a version of” some word in the longer.{Jose Luis Martinez Lopez, JL Martinez, J.L. Martinez, J Martinez, Luis Martinez, Jose Martinez, Martinez, JL, M, L} CSA4050: Information Extraction III

8. Pronouns • Most pronouns refer to an antecedent which occurs earlier in the text (not necessarily in the same sentence).John came into the room. He shivered. • The pronoun is said to be in an anaphoric relation to the antecedent. • Determination of reference can require large amounts of knowledge processing. The police refused the demonstrators a permit because they feared/advocated violence. CSA4050: Information Extraction III

9. Anaphor versus Coreference • Anaphoric and coreferential relations often coincide, but: • Not all coreferential relations are anaphoric:The Rector made his speech. Ellul-Micallef, 55 • Not all anaphoric relations are coreferential.Every man loves his mother. • Use substitution test to determine whether there is co-reference. If there is a change in meaning then expressions do not corefer.Every man loves every man’s mother CSA4050: Information Extraction III

10. Descriptions • Definite DescriptionsThe Armonk based giantThe head honcho at MicrosoftThe richest man in the world • Indefinite DescriptionsA rogue stateSome participants arrived. When they left… CSA4050: Information Extraction III

11. Indefinite Noun Phrases • Indefinites usually introduce new referents into text and are therefore unlikely to refer to earlier items.A cat crept into the room. It leaped out. • There are exceptions: when indefinites refer to a classCars are fast. A car can reach 200 kph. CSA4050: Information Extraction III

12. Example Motor Vehicles International Ltd. announced a major management shakeup. MVI said that its CEO had resigned. The big automaker is attempting to regain market share. It will announce significant losses for the third quarter. Acompany spokesman said thecompany will be moving their operations. CSA4050: Information Extraction III

13. Two Approaches to Coreference • Knowledge Engineering • Based on adapting theoretical work on coreference to the sparse and incomplete analyses obtained in IE. • Automatically Trained Systems • Small range of approaches • Probabilistic and non-probabilistic CSA4050: Information Extraction III

14. Algorithm - KE Approach • Identify each noun phrase • Mark each noun phrase with • type information, animacy etc. • agreement info (number/gender) • syntactic features (definiteness) • possibly other semantic information from dictionary (e.g. vehicle/furniture/transport) CSA4050: Information Extraction III

15. Algorithm – KE Approach • Try to distinguish between referring expressions and referents • Length • Syntactic criteria (proper noun/description) • Internal Structure • Gazetteer • For each referring expression • Determine accessible antecedents • Filter with type check • Rank candidates CSA4050: Information Extraction III

16. Accessibility Antecedents • Names – entire preceding text – possibly other documents in collection. • Match using aliases/acronyms • Definite noun phrases – part of the preceding text • same sentence; previous sentence; previous paragraph etc. • Pronouns – same but smaller stretches of preceding text (pronouns rarely refer across paragraph boundaries). CSA4050: Information Extraction III

17. Filter for Semantic Consistency • Number/GenderJohn lost Mary's trousers. Then he/she found them/her • Semantic TypeJohn dropped the hammer on the glass table. It shattered/bounced. Mike tried to save CSAI. The Department was burning. The chief acted heroically. CSA4050: Information Extraction III

18. State of the Art • MUC6 – precision .72, recall .63 • MUC7 – UPENN's high precision system, precision = .80, recall = .30 • The fact that IE parsers are incomplete, shallow and not fully reliable motivates the statistical appraches. CSA4050: Information Extraction III

19. Statistical Approaches • Motivated by errors introduced by earlier processing • Supervised learning • Data: determine, by inspection, correct coreference or classes. CSA4050: Information Extraction III

20. Methodology of Statistical Methods • Produce tagged data in which all coreference pairs are tagged as such. • Determine which system-recognisable features of the individual expressions are relevant to the co-reference judgement. • Apply some learning technique to the resulting feature vectors. CSA4050: Information Extraction III

21. UMASS RESOLVE(McCarthy & Lenhert 1995) • Which features of phrases to look for when determining coreference • How to combine evidence (+ve and –ve)? • Accumulation of errors arising from earlier stages of processing rather than from coreference procedures. • RESOLVE uses a decision tree based on Quinlan’s C4.5 system, induced from training examples, to decide whether pre-established pairs of referents are likely to be coreferents. CSA4050: Information Extraction III

22. Resolve Method • Extract references along with coreference links from text using CMI (coref. marking interf. tool). • Create all possible pairings of references, and reduce elements of each pair to a feature vectors (patterns, POS tags, semantic features, context) • Coreferent pairs are +ve instances (others are –ve instances) • RESOLVE then trained on different partitions of the set of feature vectors. CSA4050: Information Extraction III

23. Example FAMILYMART CO. OF SEIBU SAISON GROUP WILL OPEN A CONVENIENCE STORE IN TAIPEI FRIDAY IN A JOINT VENTURE WITH TAIWAN’S LARGEST CAR DEALER, THE COMPANY SAID WEDNESDAY CSA4050: Information Extraction III

24. Information Available via CMI (:string “FAMILYMART CO.” :slots (ENTITY (name “FAMILYMART CO.”) (type COMPANY) (relationship JV-PARENT CHILD))) (:string “TAIWAN’S LARGEST CAR DEALER.” :slots (ENTITY (type COMPANY) (relationship JV-PARENT) (nationality “Taiwan (COUNTRY)”))) CSA4050: Information Extraction III

25. Feature Vectors forFAMILYMART Co./TAIWAN’S LARGEST CAR DEALER CSA4050: Information Extraction III

26. Decision Tree(after McCarthy & Lenhert 1995)

27. MUC-5 Rules • IF both tokens contain the same company name THEN they are coreferent • IF both tokens contain the different company names THEN they are not coreferent • IF both tokens contain a common phrase THEN they are coreferent CSA4050: Information Extraction III

28. Results CSA4050: Information Extraction III