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NEVER-ENDING LANGUAGE LEARNER Student: Nguyễn Hữu Thành Phạm Xuân Khoái Vũ Mạnh Cầm Instructor: PhD Lê Hồng Phương Hà Nội, April 24 2014.

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Presentation on theme: "NEVER-ENDING LANGUAGE LEARNER Student: Nguyễn Hữu Thành Phạm Xuân Khoái Vũ Mạnh Cầm Instructor: PhD Lê Hồng Phương Hà Nội, April 24 2014."— Presentation transcript:

1 NEVER-ENDING LANGUAGE LEARNER Student: Nguyễn Hữu Thành Phạm Xuân Khoái Vũ Mạnh Cầm Instructor: PhD Lê Hồng Phương Hà Nội, April 24 2014

2 Ontology  Category: cities, companies, sport teams….  Relation: hasOfficeIn(organisation, location) Instance Idea: Structuring Knowledge Base

3 Globe and Mail Stanley Cup hockey NHL Toronto CFRB Wilson play hired won Maple Leafs home town city paper league Sundin Milson writer radio Maple Leaf Gardens team stadium Canada city stadium politician country Miller airport member Toskala Pearson Skydome Connaught Sunnybrook hospital city company skateshelmet uses equipment won Red Wings Detroi t hometown GM city company competes with Toyota plays in league Prius Corrola created Hino acquired automobile economic sector city stadium Idea: Structuring Knowledge Base climbing football uses equipment

4 NELL Architecture 3 2 1 Beliefs Candidate facts Knowledge Integrator CPL RL CMC CSEAL Data Resources Knowledge Base Subsystem Components

5 CPL Beliefs Candidate facts CPL Data Resources Knowledge Base

6 Belief Ontology ◦ Category ◦ Relation Instance Contextual pattern for each Ontology: Category: ontology(obj1): company  arg1 and other software company. Relation: relation: playsFor(obj1,obj2)  arg1 scored a goal for arg2.

7 Idea: Build a structuring KB using CPL. Input  Seed patterns  Seed instances  Text corpus Output  New instances  New patterns

8 Extracting Candidates 1. Category Instance Category Pattern Text corpus New category instance Example: Category Pattern: If thành_ph ố arg1 then thành_ph ố (arg1) In text corpus: thành_ph ố Đà_N ẵ ng, thành_ph ố Hà_N ộ i…. New category instances: thành_ph ố (Đà_N ẵ ng), thành_ph ố (Hà_N ộ i)

9 Extracting Candidates 2. Category Pattern Category Instance Text corpus New category pattern Example: Category instances: c ầ u_th ủ (Công Vinh), c ầ u_th ủ (H ồ ng S ơ n)… In text corpus: Công_Vinh ghi_bàn, H ồ ng_S ơ n ghi_bàn…. New category pattern: If arg1 ghi_bàn then c ầ u_th ủ (arg1)

10 Extracting Candidates 3. Relation Instance Relation pattern Text corpus New relation instance Example: Relation Pattern: If arg1 vô_ đ ị ch arg2 then tham_d ự (arg1,arg2) In text corpus: MU vô_ đ ị ch Ngo ạ i_h ạ ng_Anh New relation instance: tham_d ự (MU,Ngo ạ i_h ạ ng_Anh)

11 Extracting Candidates 4. Relation Pattern Relation instance Text corpus New relation pattern Example: Relation Pattern: ch ơ i_bóng_cho(H ồ ng_S ơ n, Th ể _Công), ch ơ i_bóng_cho(Công_Vinh, Ngh ệ _An)… In text corpus: H ồ ng_S ơ n ghi bàn cho Th ể _Công, Công_Vinh ghi bàn cho Ngh ệ _An…. New relation instance: If arg1 ghi bàn cho arg2 then ch ơ i_bóng_cho(arg1, arg2)

12 Knowledge Base

13

14 Demo


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