Triple

T15133122
Position Surface form Disambiguated ID Type / Status
Subject En Vogue E361470 entity
Predicate member P10 FINISHED
Object Cindy Herron E1003860 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: Cindy Herron | Statement: [En Vogue, member, Cindy Herron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cindy Herron
Context triple: [En Vogue, member, Cindy Herron]
  • A. Cindy Herron chosen
    Cindy Herron is an American singer and actress best known as a founding member of the R&B/pop group En Vogue.
  • B. Cindy Morgan
    Cindy Morgan is an American actress best known for her roles in the comedy film "Caddyshack" and the science fiction film "Tron."
  • C. Cindy Holland
    Cindy Holland is a television executive best known for her influential role in developing and overseeing original content at Netflix.
  • D. Cindy Henderson
    Cindy Henderson is an actress best known for voicing Wednesday Addams in the 1970s animated adaptation of The Addams Family.
  • E. Cindy Mancini
    Cindy Mancini is the popular high school cheerleader in the 1987 teen romantic comedy film "Can't Buy Me Love," whose deal with a nerdy classmate sparks unexpected personal and social consequences.
  • 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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005b29a4c819087f8818e3f5788f5 completed April 15, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb590b5cc8190b5f586e0fd2988f6 completed May 9, 2026, 10:30 p.m.
Created at: April 10, 2026, 3:06 a.m.