Triple

T10573850
Position Surface form Disambiguated ID Type / Status
Subject Dragnet (film, 1987) E249560 entity
Predicate starring P1507 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: [Dragnet (film, 1987), starring, Tom Hanks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Hanks
Context triple: [Dragnet (film, 1987), starring, 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. Jim Hanks
    Jim Hanks is an American actor and voice actor, known for frequently voicing Woody in Toy Story-related projects and for being the younger brother of Tom Hanks.
  • C. Hanks
    Hanks is a surname most prominently associated with the American acting family that includes Tom Hanks and his daughter Elizabeth Hanks.
  • D. Thomas C. Hanks
    Thomas C. Hanks is an American seismologist known for co-developing the moment magnitude scale used to measure earthquake size.
  • E. 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.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5274929cc81909a79d5e2049f7389 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b5d89748190bb398943e4a16e9b completed April 10, 2026, 7:11 p.m.
Created at: April 6, 2026, 12:37 p.m.