Triple

T1905207
Position Surface form Disambiguated ID Type / Status
Subject Passumpsic, Vermont, United States E37785 entity
Predicate state P87 FINISHED
Object Vermont E9978 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: Vermont | Statement: [Passumpsic, Vermont, United States, state, Vermont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vermont
Context triple: [Passumpsic, Vermont, United States, state, Vermont]
  • A. Vermont chosen
    Vermont is a small, rural New England state in the northeastern United States, known for its Green Mountains, maple syrup production, and picturesque towns.
  • B. New Hampshire
    New Hampshire is a small New England state in the northeastern United States known for its mountainous landscapes, early presidential primary, and “Live Free or Die” motto.
  • C. Maine
    Maine is a northeastern U.S. state known for its rugged coastline, maritime history, and vast forested interior.
  • D. Maine
    Maine is a historical region in northwestern France that played a significant role in the medieval power struggles between the English and French crowns.
  • E. Warren, Vermont
    Warren, Vermont is a small New England town in the Mad River Valley known for its scenic mountain setting, outdoor recreation, and proximity to Sugarbush Resort.
  • 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb191b710819091a5b767550fcf61 completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4e4b980888190a7df10662789f61e completed March 14, 2026, 4:31 a.m.
Created at: March 4, 2026, 7:35 p.m.