Triple

T3450802
Position Surface form Disambiguated ID Type / Status
Subject SIGKDD Service Award E72788 entity
Predicate notableRecipient P108 FINISHED
Object Christos Faloutsos E356900 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Christos Faloutsos | Statement: [SIGKDD Service Award, notableRecipient, Christos Faloutsos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christos Faloutsos
Context triple: [SIGKDD Service Award, notableRecipient, Christos Faloutsos]
  • A. Christos Faloutsos chosen
    Christos Faloutsos is a prominent computer scientist known for his influential research in data mining, database systems, and graph analytics.
  • B. Rakesh Agrawal
    Rakesh Agrawal is a pioneering computer scientist best known for his foundational contributions to data mining and database systems.
  • C. Gregory Piatetsky-Shapiro
    Gregory Piatetsky-Shapiro is a pioneering computer scientist and data mining expert best known as the founder of the KDD (Knowledge Discovery and Data Mining) conferences and the KDnuggets data science community.
  • D. Jure Leskovec
    Jure Leskovec is a prominent computer scientist known for his influential work in data mining, social network analysis, and machine learning, particularly on large-scale graph data.
  • E. Jon Kleinberg
    Jon Kleinberg is a prominent computer scientist known for his influential work in algorithms, networks, and data science, particularly in the analysis of large-scale social and information networks.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad85b05c848190b7a28ceec2bd7b74 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adba7324508190b07943cec3ecdb59 completed March 8, 2026, 6:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360eb7ad08190865e62228365d530 completed March 13, 2026, 12:57 a.m.
Created at: March 8, 2026, 3:16 p.m.