Triple

T3838461
Position Surface form Disambiguated ID Type / Status
Subject Vermont Agency of Transportation E93392 entity
Predicate locatedIn P40 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: [Vermont Agency of Transportation, locatedIn, Vermont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vermont
Context triple: [Vermont Agency of Transportation, locatedIn, 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. 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.
  • D. 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.
  • E. Maine
    Maine is a northeastern U.S. state known for its rugged coastline, maritime history, and vast forested interior.
  • 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_69aed96ce578819084ab16e3439976c9 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeeb9d11f081909fc51e84657ec7f1 completed March 9, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5626f1848819081f1b6e0128a8e91 completed March 14, 2026, 1:28 p.m.
Created at: March 9, 2026, 3:18 p.m.