Triple

T2892500
Position Surface form Disambiguated ID Type / Status
Subject Chet Hanks E63859 entity
Predicate birthName P65 FINISHED
Object Chester Marlon Hanks E63859 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: Chester Marlon Hanks | Statement: [Chet Hanks, birthName, Chester Marlon Hanks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chester Marlon Hanks
Context triple: [Chet Hanks, birthName, Chester Marlon Hanks]
  • A. Chet Hanks chosen
    Chet Hanks is an American actor and musician, known both for his roles in film and television and for being the son of actor Tom Hanks.
  • B. Tom Hanks
    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."
  • C. Colin Hanks
    Colin Hanks is an American actor and filmmaker known for roles in projects such as "Orange County," "Fargo," and "Life in Pieces."
  • D. John C. Reilly
    John C. Reilly is an American actor known for his versatile performances in both dramatic films and broad comedies, including roles in movies like "Chicago," "Boogie Nights," and "Step Brothers."
  • E. Greg Kinnear
    Greg Kinnear is an American actor and former television host known for his versatile performances in films such as "As Good as It Gets," "Little Miss Sunshine," and numerous romantic comedies.
  • 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_69ab4c45822c8190830c5f2bb97bcfd0 completed March 6, 2026, 9:51 p.m.
NER Named-entity recognition batch_69abe060f49c8190bc804614a141c738 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b055f88608819087f258286b2e9e66 completed March 10, 2026, 5:33 p.m.
Created at: March 6, 2026, 10:07 p.m.