Triple

T2590918
Position Surface form Disambiguated ID Type / Status
Subject Maura Healey E58118 entity
Predicate name P16 FINISHED
Object Maura Healey E58118 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: Maura Healey | Statement: [Maura Healey, name, Maura Healey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maura Healey
Context triple: [Maura Healey, name, Maura Healey]
  • A. Maura Healey chosen
    Maura Healey is an American politician and attorney who became the first woman and first openly lesbian governor of Massachusetts.
  • B. Nancy Hayes Sununu
    Nancy Hayes Sununu is the wife of former New Hampshire governor and White House Chief of Staff John H. Sununu and the matriarch of the prominent Sununu political family.
  • C. Martin Hynes
    Martin Hynes is an American screenwriter and filmmaker best known for co-writing the story for Pixar’s animated film "Toy Story 4."
  • D. Valerie Sununu
    Valerie Sununu is an American educator and the First Lady of New Hampshire, known for her advocacy on issues such as literacy and children's mental health.
  • E. Martha Coakley
    Martha Coakley is an American lawyer and politician who served as Attorney General of Massachusetts and was the Democratic nominee in the state's 2010 U.S. Senate and 2014 gubernatorial races.
  • 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_69ab4ac019c8819094add11c46706e32 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd40075f08190b760cb41c1417169 completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69af6589a9c48190b16b5b7959096aab completed March 10, 2026, 12:27 a.m.
Created at: March 6, 2026, 9:49 p.m.