Triple

T13099502
Position Surface form Disambiguated ID Type / Status
Subject Ann Huntress Lamont E310679 entity
Predicate name P16 FINISHED
Object Ann Huntress Lamont E310679 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: Ann Huntress Lamont | Statement: [Ann Huntress Lamont, name, Ann Huntress Lamont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ann Huntress Lamont
Context triple: [Ann Huntress Lamont, name, Ann Huntress Lamont]
  • A. Ann Huntress Lamont chosen
    Ann Huntress Lamont is an American venture capitalist and philanthropist, known as a founding partner of Oak HC/FT and the wife of Connecticut Governor Ned Lamont.
  • B. Ruth Cameron
    Ruth Cameron is an American jazz singer and producer known for her work with and marriage to renowned bassist Charlie Haden.
  • C. Elizabeth Campbell
    Elizabeth Campbell was the wife of renowned American photographer, filmmaker, and writer Gordon Parks.
  • D. Sarah MacKenzie
    Sarah MacKenzie is a tough, principled Marine Corps lawyer and one of the central protagonists in the military legal drama series JAG.
  • E. Anna Hill Johnstone
    Anna Hill Johnstone was an American costume designer renowned for her work on influential mid-20th-century films, including collaborations with major directors and contributions to gritty, realistic cinema.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d981500d34819097037b3c3c33627b completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d61bcfe88190866b4330d1669602 completed May 3, 2026, 4:59 a.m.
Created at: April 9, 2026, 9:04 p.m.