Triple

T14815453
Position Surface form Disambiguated ID Type / Status
Subject Constance Bennett E348300 entity
Predicate placeOfDeath P21 FINISHED
Object Fort Dix E600094 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: Fort Dix | Statement: [Constance Bennett, placeOfDeath, Fort Dix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fort Dix
Context triple: [Constance Bennett, placeOfDeath, Fort Dix]
  • A. Fort Dix chosen
    Fort Dix is a major U.S. Army installation in New Jersey that has long served as a key training and mobilization center for American soldiers.
  • B. Fort Richardson
    Fort Richardson was a former United States Army post near Anchorage, Alaska, that later became part of Joint Base Elmendorf–Richardson.
  • C. Buckley Garrison
    Buckley Garrison is a United States Space Force installation and unit responsible for space operations and support activities at Buckley Space Force Base in Colorado.
  • D. Fort Bragg
    Fort Bragg is a major U.S. Army installation in North Carolina known as one of the world’s largest military bases and a central hub for airborne and special operations forces.
  • E. Fort Bragg
    Fort Bragg is a small coastal city in Northern California known for its scenic Pacific shoreline, Glass Beach, and historic lumber industry.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe0e89c81908c0e1fe2bc3ebcfc completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe389598848190ba15e6eea2ba2903 completed May 8, 2026, 7:25 p.m.
Created at: April 10, 2026, 1:49 a.m.