Triple

T14657362
Position Surface form Disambiguated ID Type / Status
Subject Tom McCarthy E344144 entity
Predicate notableWork P4 FINISHED
Object Win Win E297482 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: Win Win | Statement: [Tom McCarthy, notableWork, Win Win]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Win Win
Context triple: [Tom McCarthy, notableWork, Win Win]
  • A. Win Win chosen
    Win Win is a 2011 indie dramedy film about a struggling attorney and high school wrestling coach who takes in a teenage runaway, featuring a critically acclaimed performance by Paul Giamatti.
  • B. Tell to Win
    "Tell to Win" is a business and leadership book by Hollywood executive Peter Guber that explains how strategic storytelling can be used to persuade, inspire, and drive success.
  • C. Two Can Win
    "Two Can Win" is a soulful, sample-driven hip-hop track by J Dilla from his acclaimed album "Donuts."
  • D. The Joy of Winning
    "The Joy of Winning" is a popular science book by mathematician and broadcaster Hannah Fry that explores how mathematical principles and game theory shape decision-making, competition, and everyday life.
  • E. Win Some, Lose Some
    "Win Some, Lose Some" is a reflective hip-hop track by Big Sean that explores personal struggles, growth, and the costs of success.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb51a562c819098971447db4b29f7 completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5e01cd081909c71fdcf67c3b1f5 completed May 8, 2026, 12:24 p.m.
Created at: April 10, 2026, 1:27 a.m.