Triple

T6589303
Position Surface form Disambiguated ID Type / Status
Subject Joe E159307 entity
Predicate notableWork P4 FINISHED
Object Good Girls E319400 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: Good Girls | Statement: [Joe, notableWork, Good Girls]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Good Girls
Context triple: [Joe, notableWork, Good Girls]
  • A. Good Girls chosen
    Good Girls is an American dark comedy-drama television series about three suburban mothers who turn to crime to solve their financial problems.
  • B. Very Good Girls
    Very Good Girls is a 2013 coming-of-age drama film about two best friends whose bond is tested when they fall for the same young man.
  • C. Good Girls, Bad Guys
    "Good Girls, Bad Guys" is a hip-hop track by DMX from his 1999 album "...And Then There Was X."
  • D. Calendar Girls
    Calendar Girls is a 2003 British comedy-drama film, inspired by a true story, about a group of middle-aged women who pose nude for a charity calendar.
  • E. 2 Broke Girls
    2 Broke Girls is an American sitcom that follows the comedic misadventures of two financially struggling waitresses trying to start a cupcake business in Brooklyn.
  • 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_69c688366ce8819083f8883983c0df92 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6aeb201e88190808cf5779349f96c completed March 27, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d57bde388190919ff6820e1b9610 completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:55 p.m.