Triple

T5861567
Position Surface form Disambiguated ID Type / Status
Subject Twilight E130285 entity
Predicate filmAdaptationScreenwriter P15305 FINISHED
Object Melissa Rosenberg E196044 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: Melissa Rosenberg | Statement: [Twilight, filmAdaptationScreenwriter, Melissa Rosenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melissa Rosenberg
Context triple: [Twilight, filmAdaptationScreenwriter, Melissa Rosenberg]
  • A. Melissa Rosenberg chosen
    Melissa Rosenberg is an American screenwriter and producer best known for adapting the Twilight Saga films and creating the Marvel television series Jessica Jones.
  • B. Melissa Cohen
    Melissa Cohen is a South African-born filmmaker and activist best known as the wife of Hunter Biden, son of U.S. President Joe Biden.
  • C. Melissa Stark
    Melissa Stark is an American television sportscaster best known for her work as a sideline reporter on NFL broadcasts.
  • D. Rachel Leibowitz
    Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
  • E. Melissa Parmenter
    Melissa Parmenter is a British composer and producer known for her film scores and frequent collaborations with director Michael Winterbottom.
  • 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_69c0084f3bb08190a7720f55f7aa4252 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03589f74881908cfa4f250263b97d completed March 22, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64096580481909a253f26b9535d9f completed March 27, 2026, 8:32 a.m.
Created at: March 22, 2026, 3:56 p.m.