Triple

T10527484
Position Surface form Disambiguated ID Type / Status
Subject Lopez vs Lopez E248343 entity
Predicate executiveProducer P7225 FINISHED
Object Debby Wolfe E908247 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: Debby Wolfe | Statement: [Lopez vs Lopez, executiveProducer, Debby Wolfe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Debby Wolfe
Context triple: [Lopez vs Lopez, executiveProducer, Debby Wolfe]
  • A. Debby Wolfe chosen
    Debby Wolfe is a television writer and producer best known for creating the NBC sitcom "Lopez vs Lopez" and her work on various comedy series.
  • B. Debra Humphries
    Debra Humphries is the mother of former NBA player Kris Humphries.
  • C. Debbie Meadows
    Debbie Meadows is an American political figure and businesswoman best known as the wife of former White House Chief of Staff and congressman Mark Meadows.
  • D. Debra Wilson
    Debra Wilson is an American actress and comedian best known for her groundbreaking work on the sketch comedy series MADtv and her extensive voice acting in animation and video games.
  • E. Debby Bishop
    Debby Bishop is a British actress best known for her work in film and television during the 1980s, including a role in the cult biographical drama "Sid and Nancy."
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509f5ec348190875c8c877e70ba4a completed April 7, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6e6968aec8190a9d1e51ac7e87853 completed April 21, 2026, 2:53 a.m.
Created at: April 6, 2026, 12:29 p.m.