Triple

T1714665
Position Surface form Disambiguated ID Type / Status
Subject The Green Mile E37262 entity
Predicate filmAdaptationStar P795 FINISHED
Object Tom Hanks E10383 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: Tom Hanks | Statement: [The Green Mile, filmAdaptationStar, Tom Hanks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Hanks
Context triple: [The Green Mile, filmAdaptationStar, Tom Hanks]
  • A. Tom Hanks chosen
    Tom Hanks is an acclaimed American actor and filmmaker renowned for his versatile performances in films such as "Forrest Gump," "Saving Private Ryan," and "Cast Away."
  • B. George Clooney
    George Clooney is an American actor, filmmaker, and activist renowned for his work in film and television as well as his humanitarian and political advocacy.
  • C. Richard Gere
    Richard Gere is an American actor known for his leading roles in films such as "American Gigolo," "An Officer and a Gentleman," and "Pretty Woman."
  • D. Kevin Bacon
    Kevin Bacon is an American actor and producer known for his versatile film and television roles and for inspiring the pop-culture concept of "Six Degrees of Kevin Bacon."
  • E. James Woods
    James Woods is an American actor known for his intense performances in film and television, including acclaimed roles in movies such as "Salvador," "Videodrome," and "Casino."
  • 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_69a8861912dc8190931af43b4b9158a7 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa633349248190822e560fde817fc7 completed March 6, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69adb5be1a2c819083b95d55c969b9d6 completed March 8, 2026, 5:45 p.m.
Created at: March 4, 2026, 7:30 p.m.