Post on 15-Jan-2016
description
December 2003 CSA4050: Information Extraction III 1
CSA4040:Advanced Topics in NLP
Information Extraction III
Coreference
December 2003 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
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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?
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Different Kinds of Noun Phrase
• Proper Nouns– Single Word– Multiple Word
• Pronouns
• Descriptions– Definite– Indefinite
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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> ...
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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
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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}
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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.
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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
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Descriptions
• Definite DescriptionsThe Armonk based giantThe head honcho at MicrosoftThe richest man in the world
• Indefinite Descriptions A rogue stateSome participants arrived. When they left…
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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.
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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. A company spokesman said the company will be moving their operations.
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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
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Algorithm - KE Approach
1. Identify each noun phrase
2. 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)
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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
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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).
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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.
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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.
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Statistical Approaches
• Motivated by errors introduced by earlier processing
• Supervised learning
• Data: determine, by inspection, correct coreference or classes.
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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.
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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.
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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.
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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
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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)”)))
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Feature Vectors forFAMILYMART Co./TAIWAN’S LARGEST CAR DEALER
Individual Phrases Pair of Phrases
Attribute Value Attribute Value
NAME-1 YES ALIAS NO
JV-CHILD-1 NO BOTH-JV-CHLD NO
NAME-2 YES COMMON-NP NO
JV-CHILD-2 NO SAME-SENT YES
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Decision Tree(after McCarthy & Lenhert 1995)
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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
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Results