Triple

T11859696
Position Surface form Disambiguated ID Type / Status
Subject Legally Blonde (Broadway musical) E282128 entity
Predicate producer P490 FINISHED
Object Hal Luftig E416734 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: Hal Luftig | Statement: [Legally Blonde (Broadway musical), producer, Hal Luftig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hal Luftig
Context triple: [Legally Blonde (Broadway musical), producer, Hal Luftig]
  • A. Hal Luftig chosen
    Hal Luftig is a prominent American theatrical producer known for his work on major Broadway shows, including multiple Tony Award–winning productions.
  • B. Uri Nodelman
    Uri Nodelman is a philosopher and academic best known for serving as editor-in-chief of the Stanford Encyclopedia of Philosophy, a leading online reference in the field.
  • C. M.G. Siegler
    M.G. Siegler is a technology writer and venture capitalist known for his work at TechCrunch and his investing role at Google Ventures (GV).
  • D. Morton Heiligman
    Morton Heiligman is an academic known for supervising the doctoral work of computer scientist and Smalltalk pioneer Adele Goldberg.
  • E. Robert L. May
    Robert L. May was an American copywriter and author best known for creating the Christmas character Rudolph the Red-Nosed Reindeer.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a69a099c8190a674db64c50eca5a completed April 10, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69f281745ca88190968e1f674d0e483c completed April 29, 2026, 10:08 p.m.
Created at: April 8, 2026, 9:43 p.m.