Triple

T500224
Position Surface form Disambiguated ID Type / Status
Subject Tom Hanks E10383 entity
Predicate birthName P65 FINISHED
Object Thomas Jeffrey 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: Thomas Jeffrey Hanks | Statement: [Tom Hanks, birthName, Thomas Jeffrey Hanks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas Jeffrey Hanks
Context triple: [Tom Hanks, birthName, Thomas Jeffrey 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. 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."
  • D. Tim Robbins
    Tim Robbins is an American actor, director, and producer best known for his roles in films such as The Shawshank Redemption, Mystic River, and Bull Durham.
  • E. Brad Pitt
    Brad Pitt is an American actor and film producer renowned for his leading roles in major Hollywood films and for winning multiple Academy Awards.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f13096248190a622a58dcf540b00 completed Feb. 28, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a48a79ef808190a9dc34b58e16a160 completed March 1, 2026, 6:50 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.