Triple

T19982118
Position Surface form Disambiguated ID Type / Status
Subject Squyres E493841 entity
Predicate hasNotableBearer P458 FINISHED
Object Tim Squyres NE NERFINISHED

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: Tim Squyres | Statement: [Squyres, hasNotableBearer, Tim Squyres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tim Squyres
Context triple: [Squyres, hasNotableBearer, Tim Squyres]
  • A. Tim Squyres chosen
    Tim Squyres is an American film editor best known for his long-time collaboration with director Ang Lee on acclaimed films such as "Crouching Tiger, Hidden Dragon" and "Life of Pi."
  • B. Daniel Sleator
    Daniel Sleator is a computer scientist known for his contributions to data structures and algorithms, including the development of splay trees.
  • C. Chris Galletta
    Chris Galletta is an American screenwriter best known for writing the coming-of-age comedy film "The Kings of Summer."
  • D. Paul Quattrone
    Paul Quattrone is an American drummer best known for his work with experimental and garage rock bands, including Thee Oh Sees.
  • E. Doug Sweeney
    Doug Sweeney is a scholar of American religious history known for his work on Jonathan Edwards and evangelicalism.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626a67648190af9653832a3aeced completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e65d13a8a88190bf5f4f697793f4c9 completed April 20, 2026, 5:06 p.m.
Created at: April 11, 2026, 3:28 p.m.