Triple

T8572783
Position Surface form Disambiguated ID Type / Status
Subject Warren, Vermont E202968 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: [Warren, Vermont, state, Vermont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vermont
Context triple: [Warren, 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. 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. New Hampshire and Maine
    New Hampshire and Maine are neighboring New England states in the northeastern United States, known for their rugged coastlines, forested landscapes, and historic colonial towns.
  • 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_69ca8327b0a881908606ff860713964d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbea43843c8190ac2224d427bb7a75 completed March 31, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce88498cf081909c25c292c014fe8c completed April 2, 2026, 3:16 p.m.
Created at: March 30, 2026, 6:21 p.m.