Triple

T13392670
Position Surface form Disambiguated ID Type / Status
Subject Young at Heart E319613 entity
Predicate setInLocation P40 FINISHED
Object Connecticut E10549 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: Connecticut | Statement: [Young at Heart, setInLocation, Connecticut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Connecticut
Context triple: [Young at Heart, setInLocation, Connecticut]
  • A. Connecticut chosen
    Connecticut is a small New England state in the northeastern United States known for its colonial history, affluent suburbs, and role as a financial and educational hub.
  • B. Rhoda Island
    Rhoda Island is a Nile island in central Cairo, Egypt, known for its historic palaces, gardens, and cultural landmarks.
  • C. Vermont
    Vermont is a small, rural New England state in the northeastern United States, known for its Green Mountains, maple syrup production, and picturesque towns.
  • D. Vermont
    Vermont is a small rural town located in Dane County, Wisconsin, known for its scenic landscapes and agricultural character.
  • E. Scotland, Connecticut
    Scotland, Connecticut is a small rural town in eastern Windham County known for its historic character and quiet, agricultural landscape.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dba0d74e5881909828854bba7d9a87 completed April 12, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73051273c81909eb91c923f37557e completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:34 p.m.