Triple

T9218047
Position Surface form Disambiguated ID Type / Status
Subject Wells River, Vermont E221289 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: [Wells River, Vermont, state, Vermont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vermont
Context triple: [Wells River, Vermont, 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. Vermont
    Vermont is a small rural town located in Dane County, Wisconsin, known for its scenic landscapes and agricultural character.
  • C. Washington, Vermont
    Washington, Vermont is a small rural town in central Vermont known for its scenic landscapes and traditional New England character.
  • D. 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.
  • E. New Hampshire and Vermont
    New Hampshire and Vermont are two neighboring New England states in the northeastern United States, known for their rural landscapes, small towns, and shared border along the Connecticut River.
  • 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_69ca83eae42c8190a0ea9e040710a277 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda0ae3d081908ff3f5dab52df5ae completed April 1, 2026, 8:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69d065c0d77081908fd707af138218fd completed April 4, 2026, 1:13 a.m.
Created at: March 30, 2026, 7:27 p.m.