Triple

T13988213
Position Surface form Disambiguated ID Type / Status
Subject Mary Moore E336497 entity
Predicate hasLastName P18 FINISHED
Object Moore E32614 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: Moore | Statement: [Mary Moore, hasLastName, Moore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moore
Context triple: [Mary Moore, hasLastName, Moore]
  • A. Moore chosen
    Moore is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
  • B. Moore
    Moore is the middle name of Edward M. Kennedy, the long-serving U.S. senator from Massachusetts and prominent member of the Kennedy political family.
  • C. Moore
    Moore is a small village and civil parish in the Borough of Halton in Cheshire, England.
  • D. Moore
    Moore is a given name that served as the middle name of Fred M. Vinson, the 13th Chief Justice of the United States.
  • E. Moore
    Moore is a suburban city in central Oklahoma, located just south of Oklahoma City and known for its history of devastating tornadoes.
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ea537408190bb9d35963886803f completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac9604cc819088cde0ad8271ad48 completed May 6, 2026, 9:03 p.m.
Created at: April 9, 2026, 10:18 p.m.