Triple

T3063664
Position Surface form Disambiguated ID Type / Status
Subject Lifetime E62053 entity
Predicate notableProgram P4 FINISHED
Object Drop Dead Diva E84011 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: Drop Dead Diva | Statement: [Lifetime, notableProgram, Drop Dead Diva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Drop Dead Diva
Context triple: [Lifetime, notableProgram, Drop Dead Diva]
  • A. Drop Dead Diva chosen
    Drop Dead Diva is an American comedic drama television series that follows a shallow model who dies and is reincarnated in the body of a brilliant, plus-sized lawyer, blending legal cases with themes of identity and self-acceptance.
  • B. Drop Dead Gorgeous
    Drop Dead Gorgeous is a 1999 dark comedy mockumentary film that satirizes American beauty pageants and small-town culture.
  • C. Diva
    "Diva" is a swaggering, club-ready R&B/pop track by Beyoncé that celebrates female confidence and star power.
  • D. Drama Queen
    "Drama Queen" is a song by American punk rock band Green Day from their album ¡Tré!.
  • E. Il Divo
    Il Divo is a multinational classical crossover vocal group known for blending operatic technique with popular songs in multiple languages.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9ea088fc819090b9d5bbcb268671 completed March 8, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef118cb48190a1f666ead7c19a12 completed March 11, 2026, 10:39 p.m.
Created at: March 8, 2026, 3:02 p.m.