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Overview of Entity Discovery and Linking Tasks at KBP2014 Heng Ji (RPI) Joel Nothman, Ben Hachey (Univ. of Sydney) Thanks to KBP2014 Organizing Committee.

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Presentation on theme: "Overview of Entity Discovery and Linking Tasks at KBP2014 Heng Ji (RPI) Joel Nothman, Ben Hachey (Univ. of Sydney) Thanks to KBP2014 Organizing Committee."— Presentation transcript:

1 Overview of Entity Discovery and Linking Tasks at KBP2014 Heng Ji (RPI) Joel Nothman, Ben Hachey (Univ. of Sydney) Thanks to KBP2014 Organizing Committee

2 Goals and The Task 2

3 Overview Motivations o The most popular EL Trend: Collective Inference - disambiguate a set of relevant mentions simultaneously by leveraging the global topical coherence between entities o A lot of research has been done in parallel in the Wikification community (Bunescu, 2006) - extract prominent ngrams as concept mentions, and link each concept mention to the KB o One important research direction of KBP: “Cold-start” What’s New in 2014 o Extend English task to Entity Discovery and Linking (full Entity Extraction + Entity Linking + NIL Clustering) o Add discussion forums to Cross-lingual tracks o Share some source collections and queries with regular and cold-start slot filling tracks, to investigate the role of EDL in the entire cold-start KBP pipeline o Provide automatic annotations, reading list, software tools 3

4 Entity Mention Extraction It’s a version of Chicago – the standard classic Macintosh menu font, with that distinctive thick diagonal in the ”N”. Chicago was used by default for Mac menus through MacOS 7.6, and OS 8 was released mid Chicago VIII was one of the early 70s-era Chicago albums to catch my ear, along with Chicago II. 4

5 Clustering: Cross-doc Coreference Resolution It’s a version of Chicago – the standard classic Macintosh menu font, with that distinctive thick diagonal in the ”N”. Chicago was used by default for Mac menus through MacOS 7.6, and OS 8 was released mid Chicago VIII was one of the early 70s-era Chicago albums to catch my ear, along with Chicago II. 5

6 6 Linking: Disambiguation to KB It’s a version of Chicago – the standard classic Macintosh menu font, with that distinctive thick diagonal in the ”N”. Chicago was used by default for Mac menus through MacOS 7.6, and OS 8 was released mid Chicago VIII was one of the early 70s-era Chicago albums to catch my ear, along with Chicago II.

7 Evaluation Measures 7 Added type matching variant into each measure

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10 CEAF (Luo, 2005) Idea: a mention or entity should not be credited more than once Formulated as a bipartite matching problem o A special ILP problem o Efficient algorithm: Kuhn-Munkres

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12 Participants 12 EDL: 20 teams, 75 runs; EL: 17 teams, 55 runs

13 The Results 13

14 General Architecture 14  Feedback from linking to improve extraction  New ranking algorithm: Progamming with Personalized PageRank algorithm by CohenCMU (Mazaitis et al., 2014)  A nice summary of the state-of-the- art ranking features by Tohoku NL (Zhou et al., 2014)

15 Overall Performance: Extraction + Linking 15  Scoring: span, type and KB ID match  Systems with > 60% NERL F1 are significantly better than others (90% confidence interval)

16 Overall Performance: Extraction + Clustering 16  Scoring: span, type and clustering  LCC and RPI systems are significantly better than others (90% confidence interval)

17 Impact of Entity Mention Extraction 17  NER: span; NERC: span_type; NERL: span_type_KBID KBIDs: docid_KBID  NER (extraction) correlates with NERL (Extraction + Linking) well  Bug in IBM system 75%, Much lower than state-of- the-art name tagging (89%)

18 Diagnostic Entity Linking Performance 18  High performance with perfect entity mentions (70%  90%) IBM is somewhere here too!

19 Entity Types and Textual Genres 19  Scoring: span, type and linking  Easiest: persons and discussion forum

20 Clustering Measures 20  B-cubed is very sensitive to mention extraction errors

21 Cross-lingual Entity Linking 21  Both systems followed their English EL approaches  IBM achieved similar performance with the top English EDL system (the difficulty level of queries are not comparable)  Many Chinese teams chose to focus on English EDL (a cloned version in NLPCC2014 organized by PKU)  Tri-lingual EDL in KBP2015 QueryTeam B-cubed+ (%) P R F Spanish HITS IBM English HITS IBM

22 What’s New and What Works - Or How to Make My Advisor Happy 22  A roll-coaster-style conversation 12 hours before this presentation…  R: I started to question why we are doing all of these…  H:  Please don’t tell me all of these are meaningless…  R: Did EDL produce any new science?  H: Of course! Blabla…blabla…blabla…blabla…and Blabla  R: You make me happy

23 Entity Linking Milestones 23  2006: The first definition of Wikification task (Bunescu and Pasca, 2006)  2009: TAC-KBP Entity Linking launched (McNamee and Dang, 2009)  : Supervised learning-to-rank with diverse levels of features such as entity profiling, various popularity and similarity measures were developed (Gao et al., 2010; Chen and Ji, 2011; Ratinov et al., 2011; Zheng et al., 2010; Dredze et al., 2010; Anastacio et al., 2011) ;  : Collective Inference, Coherence measures were developed (Milne and Witten, 2008; Kulkarni et al., 2009; Ratinov et al., 2011; Chen and Ji, 2011; Ceccarelli et al., 2013; Cheng and Roth, 2013)  2012: Various applications(e.g., Knowledge Acquisition (via grounding), Coreference resolution (Ratinov and Roth, 2012) and Document classification (Vitale et al., 2012; Song and Roth, 2014; Gao et al., 2014)  2014: TAC-KBP Entity Discovery and Linking (end-to-end name tagging, cross-document entity clustering, entity linking)  : Many different versions of international evaluations were inspired from TAC-KBP; more than 130 papers have been published

24 Joint Extraction and Linking 24  Some recent work (Sil and Yates, 2013; Meij et al., 2012; Guo et al., 2013; Huang et al., 2014b) proved extraction and linking can mutually enhance each other  Bosch will provide the rear axle.  Robert Bosch Tool Corporation  ORG  Parker was 15 for 21 from the field, putting up a season high while scoring nine of San Antonio’s final 10 points in regulation  San Antonio Spurs  ORG  IBM (Sil and Florian, 2014), MSIIPL THU (Zhao et al., 2014), SemLinker (Meurs et al., 2014), UBC (Barrena et al., 2014) and RPI (Hong et al., 2014) used the properties in external KBs such as DBPedia as feedback to refine the identification and classification of name mentions.  RPI system successfully corrected 11.26% wrong mentions  HITS team (Judea et al., 2014) proposed a joint approach that simultaneously solves extraction, linking and clustering using Markov Logic Networks  Document Linking  Event Extraction (Ji and Grishman, 2008)  Entity Linking  Relation Extraction (Chan and Roth, 2010)  Toward more interactions and joint inferences between tasks  Marry EDL and SF in KBP2015

25 25 David Cone, a Kansas City native, was originally signed by the Royals and broke into the majors with the team Entity Linking to Improve Relation Extraction (Chan and Roth, 2010) David Brian Cone (born January 2, 1963) is a former Major League Baseball pitcher. He compiled an 8–3 postseason record over 21 postseason starts and was a part of five World Series championship teams (1992 with the Toronto Blue Jays and 1996, 1998, 1999 & 2000 with the New York Yankees). He had a career postseason ERA of He is the subject of the book A Pitcher's Story: Innings With David Cone by Roger Angell. Fans of David are known as "Cone-Heads." Major League BaseballpitcherWorld Series1992Toronto Blue Jays New York YankeesRoger AngellCone-Heads Cone lives in Stamford, Connecticut, and is formerly a color commentator for the Yankees on the YES Network. [1]Stamford, Connecticut color commentatorYES Network [1] Contents [hide]hide 1 Early years 2 Kansas City Royals 3 New York Mets Partly because of the resulting lack of leadership, after the 1994 season the Royals decided to reduce payroll by trading pitcher David Cone and outfielder Brian McRae, then continued their salary dump in the 1995 season. In fact, the team payroll, which was always among the league's highest, was sliced in half from $40.5 million in 1994 (fourth-highest in the major leagues) to $18.5 million in 1996 (second-lowest in the major leagues)David ConeBrian McRae1995 season1996

26 Task-specific / Genre-specific Mention Extraction 26  Extraction for Linking  4% entity mentions included nested mentions  Posters in discussion forum should be extracted  HITS (Judea et al., 2014), LCC (Monahan et al., 2014), MSIIPL THU (Zhao et al., 2014), NYU (Nguyen et al., 2014) and RPI (Hong et al., 2014) developed heuristic rules to significantly improve name tagging

27 Toward Deep Understanding of Full Documents 27  Old Query-driven Entity Linking  Limited exploration of co-occurring entity mentions  Bag-of-words style  New EDL Task  Deep representation and understanding the relations among entities in the source documents  Natural Language Understanding style  e.g., Use Abstract Meaning Representation (details in RPI’s EDL talk)

28  It was a pool report typo. Here is exact Rhodes quote: ”this is not gonna be a couple of weeks. It will be a period of days.”  At a WH briefing here in Santiago, NSA spox Rhodes came with a litany of pushback on idea WH didn’t consult with Congress.  Rhodes singled out a Senate resolution that passed on March 1st which denounced Khaddafy’s atrocities. WH says UN rez incorporates it Ben Rhodes (Speech Writer) 28 Better Meaning Representation

29 Source: No matter what, he never should have given Michael Jackson that propofol. He seems to think a “proper” court would have let Murray go free. KB: The trial of Conrad Murray was the American criminal trial of Michael Jackson's personal physician, Conrad Murray. Social Relation 29 Select Collaborators from Rich Context

30 Source: Mubarak, the wife of deposed Egyptian President Hosni Mubarak, … wife 30 Select Collaborators from Rich Context Family KB: Suzanne Mubarak (born 28 February 1941) is the wife of former Egyptian President Hosni Mubarak…

31 Source: Hundreds of protesters from various groups converged on the state capitol in Topeka, Kansas today… Second, I have a really hard time believing that there were any ACTUAL “explosives” since the news story they link to talks about one guy getting arrested for THREATENING Governor Brownback. Sam Brownback Peter Brownback 31 Select Collaborators from Rich Context Employment KB: Sam Brownback was elected Governor of Kansas in 2010 and took office in January 2011.

32 Source: AT&T coverage in GA is good along the interstates and in the major cities like Atlanta, Athens, Rome, Roswell and Albany. Rome, Georgia 32 Select Collaborators from Rich Context Part-whole KB: At the 2010 census, Rome had a total population of 36,303, and is the largest city in Northwest [Georgia] and the 19 th largest city in the state. Rome, Italy

33 Source: Going into the big Super Tuesday, Romney had won the most votes, states and delegates, Santorum had won some contests and was second, Gingrich had only one contest. Mitt RomneyGeorge W. Romney 33 Select Collaborators from Rich Context Start-position Event KB: The Super Tuesday primaries took place on March 6. Mitt Romney carried six states, Rich Santorum carried three, and Newt Gingrich won only in his home state of Georgia.

34 Graph-based NIL Entity Clustering 34  Bad News in EL2012  CUNY-BLENDER (Tamang et al., 2012) explored more than 40 clustering algorithms and found that advanced graph-based clustering algorithms did not significantly out-perform single baseline “All-in- one” clustering algorithm on the overall queries (except the most difficult ones)  Good News in EDL2014  LCC (Monahan et al., 2014) proved that graph partition based algorithm achieved significant gains.

35 Remaining Challenges 35

36 Name Tagging: “Old” Milestones 36 YearTasks & Resources MethodsF-MeasureExample References 1966-First person name tagger with punch card 30+ decision tree type rules -(Borkowski et al., 1966) 1998MUC-6MaxEnt with diverse levels of linguistic features 97.12%(Borthwick and Grishman, 1998) 2003CONLLSystem combination; Sequential labeling with Conditional Random Fields 89%(Florian et al., 2003; McCallum et al., 2003; Finkel et al., 2005) 2006ACEDiverse levels of linguistic features, Re-ranking, joint inference ~89%(Florian et al., 2006; Ji and Grishman, 2006)  Our progress compared to 1966:  More data, a few more features and more fancy learning algorithms  Not much active work after ACE because we tend to believe it’s a solved problem…

37 37 Cross-genre Name Tagging  Experiments on ACE2005 data

38 What’s Wrong? 38  Name taggers are getting old (trained from 2003 news & test on 2012 news)  Genre adaptation (informal contexts, posters)  Revisit the definition of name mention – extraction for linking  Old unsolved problems  Identification: “Asian Pulp and Paper Joint Stock Company, Lt. of Singapore”  Classification: “FAW has also utilized the capital market to directly finance,…” (FAW = First Automotive Works)  Potential Solutions for Quality  Word clustering, Lexical Knowledge Discovery (Brown, 1992; Ratinov and Roth, 2009; Ji and Lin, 2010)  Feedback from Linking, Relation, Event (Sil and Yates, 2013; Li and Ji, 2014)

39 Remaining Challenges for Linking  Remaining Challenges  Popularity bias  Knowledge gap between source and KB  Commonsense Knowledge  Potential Solutions  Deep knowledge acquisition and representation (e.g., AMR)  Better graph search alignment algorithms  Make more people excited about Chinese and Spanish by providing more resources  Tri-lingual EDL in KBP

40 Popularity Bias If you are called Michael Jordan…

41 A Little Better…

42 Source: breaking news/new information/rumors KB: bio, summary, snapshot of life Christies denial of marriage privledges to gays will alienate independents and his “I wanted to have the people vote on it” will ring hollow. Christie has said that he favoured New Jersey's law allowing same-sex couples to form civil unions, but would veto any bill legalizing same- sex marriage in New Jersey Translation out of hype-speak: some kook made threatening noises at Brownback and go arrested Samuel Dale "Sam" Brownback (born September 12, 1956) is an American politician, the 46th and current Governor of Kansas. Connect/Sort Background Knowledge Man Accused Of Making Threatening Phone Call To Kansas Gov. Sam Brownback May Face Felony Charge 42 Knowledge Gap between Source and KB

43 During talks in Geneva attended by William J. Burns Iran refused to respond to Solana’s offers. Commonsense Knowledge William_J._Burns ( ) William_Joseph_Burns (1956- ) 43

44 Conclusions and Looking Forward 44  The new EDL task has attracted much interests from the KBP community and produced some interesting research problems and new directions  KBP2015  Improve the annotation guideline and annotation quality of the training and evaluation data sets  Develop more open sources, data and resources for Spanish and Chinese EDL  Encourage researchers to re-visit the entity mention extraction problem in the new cold-start KBP setting  Propose a new tri-lingual EDL task on a source collection from three languages: English, Chinese and Spanish  Investigate the impact of EDL on the end-to-end cold-start KBP framework; joint inference between EDL and SF

45 We can do it! 45


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