Triple

T644660
Position Surface form Disambiguated ID Type / Status
Subject Samuel Fuller E11214 entity
Predicate name P16 FINISHED
Object Samuel Fuller E11214 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: Samuel Fuller | Statement: [Samuel Fuller, name, Samuel Fuller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samuel Fuller
Context triple: [Samuel Fuller, name, Samuel Fuller]
  • A. Samuel Fuller chosen
    Samuel Fuller was an English physician and prominent Pilgrim who sailed on the Mayflower and served as the chief doctor for the Plymouth Colony.
  • B. Tom Benedek
    Tom Benedek is an American screenwriter best known for co-writing the science fiction film "Cocoon."
  • C. Franklin J. Schaffner
    Franklin J. Schaffner was an American film and television director best known for acclaimed works such as "Patton," "Planet of the Apes," and "Papillon."
  • D. Arthur Penn
    Arthur Penn was an influential American film director whose innovative, character-driven works like "Bonnie and Clyde" helped define the New Hollywood era.
  • E. Hal Ashby
    Hal Ashby was an influential American film director and editor of the New Hollywood era, known for acclaimed, offbeat classics such as "Harold and Maude," "Shampoo," and "Being There."
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f19f9a08190b0bf6e19b32427ff completed March 1, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a58035296481908c177e782137b194 completed March 2, 2026, 12:19 p.m.
Created at: March 1, 2026, 7:36 p.m.