Textual RelationsTask Definition
Annotate input text with disambiguated Wikipedia titles:
Motivation
Current state-of-the-art Wikifiers, using purely statistical methods, already achieve good performance, leveling off at around 75%~80% F1• Limitation of Bag-of-words representation
Task Definition
Annotate input text with disambiguated Wikipedia titles:
Motivation
Current state-of-the-art Wikifiers, using purely statistical methods, already achieve good performance, leveling off at around 75%~80% F1• Limitation of Bag-of-words representation
Evaluations
• Achieves significant improvement over the previous state-of-the-art systems
• Run the Relational Inference Wikifier (RI) “as-is” without retraining on the target domain, still obtains significant gain over our previous submitted Entity Linking system(Cogcomp).
Discussion
Evaluations
• Achieves significant improvement over the previous state-of-the-art systems
• Run the Relational Inference Wikifier (RI) “as-is” without retraining on the target domain, still obtains significant gain over our previous submitted Entity Linking system(Cogcomp).
Discussion
Relational Wikification Approach
1. Identify Textual Relations
2. Retrieve Relational Knowledge
3. Formulate the inference problem
4. Rerank via constraints
Promote candidate pair: Slobodan_Milošević Socialist_Party_of_Serbia
Relational Inference for WikificationXiao Cheng and Dan Roth
This research is sponsored by DARPA under agreement number FA8750-13-2-0008, and partly supported by the IARPA under contract number D11PC20155, by the ARL under agreement W911NF-09-2-0053, and by the Multimodal Information Access & Synthesis Center at UIUC.
Demo: http://cogcomp.cs.illinois.edu/demo/wikify/
Blumenthal (D) is a candidate for the U.S. Senate seat now held by Christopher Dodd (D), and he has held a commanding lead in the race since he entered it. But the Times report has the potential to fundamentally reshape the contest in the Nutmeg State.Chris DoddFrom Wikipedia, the free encyclopedia
The New York TimesFrom Wikipedia, the free encyclopedia
ConnecticutFrom Wikipedia, the free encyclopedia
Democratic Party (United States)From Wikipedia, the free encyclopedia
United States SenateFrom Wikipedia, the free encyclopedia
Richard BlumenthalFrom Wikipedia, the free encyclopedia
...ousted long time Yugoslav President Slobodan Milošević in October. Mr. Milošević's Socialist Party…
ek4=Socialist Party sk
4
Socialist_Party_(France) .23Socialist_Party_(Portugal) .16Socialist_Party_of_America .07Socialist_Party_(Argentina) .06…Socialist_Party_of_Serbia .0
ek3=Milošević sk
3
Slobodan_Milošević .7Milošević_(surname) .1Boki_Milošević .1Alexander_Milošević .05…
Argument 1 Relation Type Argument 2
Yugoslav President apposition Slobodan Milošević
Slobodan Milošević coreference Milošević
Milošević possessive Socialist Party
68
72
76
80
84
88
RI
CogCompLC
C
MS_MLI
NUShime
*Median
TAC KBP 2011 Entity Linking Performance
Micro AverageB³F1
System Names
ACE MSNBC AQUAINT Wikipedia60
65
70
75
80
85
90
95
F1 Performance on Wikification datasets
Milne&WittenRatinov&RothRelational Inference
founded
Slobodan MiloševićFrom Wikipedia, the free encyclopedia
Socialist Party of SerbiaFrom Wikipedia, the free encyclopedia
Mubarak, the wife of deposed Egyptian President Hosni Mubarak, …
Mubarak
wife
Egyptian President
Hosni Mubarak
𝑟34(1,21)=1
We are interested in extracting high-precision textual relations that help with disambiguation. Specifically, we focus on the following types of relations:• Syntactico-semantic relations (Chan & Roth ‘10)
• Coreference relations• Acronyms, partial names, nominal mentions
We show that both linguistic and world knowledge, specifically the ability to use relational information, are crucial in the task of Wikification. To do that, we introduce an extensible and efficient inference framework that leverages better language understanding. Additional work is needed to accumulate and better integrate our knowledge about NIL entities to fully address the Entity Linking task and handle additional encyclopedic resources. The performance gains and error analysis also calls for joint entity typing, coreference and disambiguation.
• Bag-of-words loses important relational information
• Modeling constraining interaction between concepts• Need to link Mubarak to Suzanne
Mubarak• Identify relation (Mubarak, wife, Hosni
Mubarak)• Promote a pair of candidates that is
coherent with text meaning
• For each pair of entity candidates and , represents whether we found a relation in the text between their mentions AND a relation in our knowledge base
• either rewards or penalizes a relation for its coherency with the text.High-level algorithm description
Type ExamplePremodifier Iranian Ministry of DefensePossessive NYC’s stock exchangeFormulaic Chicago, IllinoisPreposition President of the US
Relation Retrieval• Uses DBPedia and Wikipedia page link
relations as our knowledge base• Retrieve lexically similar candidates and filter
• q1=(Socialist Party of France,?, *Milošević*)
• q2=(Slobodan Milošević,?,*Socialist Party*)
Relation Inference• Relation scoring
• Relaxes constraint when ambiguity exists• Scores each retrieved relation for each
query
• is the relation weight for different knowledge source
• is the lexical similarity between the query and the retrieved relation
• is a normalization factor, keeping the weights for each pair of mentions between 0 and 1
• Special handling of “local knowledge”• Creates NIL entity candidate for inference
propagation, so that locally extracted high precision knowledge can be considered across long-range textual relations
• Uses off-the-shelf Integer Linear Programming (ILP) packages to optimize the objective function
References:X. Cheng and D. Roth, Relational Inference for Wikification. EMNLP’13 L. Ratinov and D. Roth and D. Downey and M. Anderson, Local and Global Algorithms for Disambiguation to Wikipedia. ACL’11