Triple

T13446541
Position Surface form Disambiguated ID Type / Status
Subject Law & Order: LA E320498 entity
Predicate mainCastMember P5563 FINISHED
Object Megan Boone E773151 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: Megan Boone | Statement: [Law & Order: LA, mainCastMember, Megan Boone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Megan Boone
Context triple: [Law & Order: LA, mainCastMember, Megan Boone]
  • A. Megan Boone chosen
    Megan Boone is an American actress best known for her leading role as FBI profiler Elizabeth Keen on the television series "The Blacklist."
  • B. Gabrielle Bullock
    Gabrielle Bullock is an American architect and principal at the global firm Perkins&Will, recognized for her leadership in diversity, equity, and inclusion within the architecture profession.
  • C. Potnia Theron
    Potnia Theron is an ancient Greek title meaning "Mistress of Animals," associated especially with Artemis as a goddess who rules over and protects wild creatures.
  • D. Jessica Alba
    Jessica Alba is an American actress and businesswoman known for her roles in films like "Fantastic Four" and for founding the consumer goods company The Honest Company.
  • E. Sharley Hudson
    Sharley Hudson was the wife of American character actor Keenan Wynn.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaef5f610819092cad33ef72075ff completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73998221c8190a2d8982a3da28ec9 completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:40 p.m.