Triple

T16811065
Position Surface form Disambiguated ID Type / Status
Subject Grayson Kent E408610 entity
Predicate loveInterestOf P7325 FINISHED
Object Jane Bingum NE NERFINISHED

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: Jane Bingum | Statement: [Grayson Kent, loveInterestOf, Jane Bingum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jane Bingum
Context triple: [Grayson Kent, loveInterestOf, Jane Bingum]
  • A. Jane Bingum chosen
    Jane Bingum is the intelligent, plus-sized lawyer protagonist of the television series "Drop Dead Diva," known for combining sharp legal skills with a compassionate, quirky personality.
  • B. Lisa Rogers
    Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
  • C. Lisa Roberts Gillan
    Lisa Roberts Gillan is an American actress and producer, known for her supporting roles in film and television and for being part of the Roberts acting family that includes siblings Eric Roberts and Julia Roberts.
  • D. Jennifer Tighe
    Jennifer Tighe is an American actress known for her work in television, film, and theater, and as the daughter of actor Kevin Tighe.
  • E. Lisa Rolfe
    Lisa Rolfe is the central protagonist of the 1984 comedy-drama film "Garbo Talks," around whom the story’s emotional and narrative developments revolve.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2d0793c81909d938ac174a6e63a completed April 18, 2026, 4:35 p.m.
Created at: April 10, 2026, 5:23 a.m.