Triple

T4398072
Position Surface form Disambiguated ID Type / Status
Subject Manchester, Vermont E99540 entity
Predicate nearestCity P350 FINISHED
Object Rutland, Vermont E163469 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: Rutland, Vermont | Statement: [Manchester, Vermont, nearestCity, Rutland, Vermont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rutland, Vermont
Context triple: [Manchester, Vermont, nearestCity, Rutland, Vermont]
  • A. Rutland, Vermont chosen
    Rutland, Vermont is a small city in central Vermont known as a regional commercial hub and gateway to nearby Green Mountain ski areas and outdoor recreation.
  • B. 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.
  • C. St. George, Vermont
    St. George, Vermont is a small town in northwestern Vermont known for being the least populous town in Chittenden County.
  • D. Rupert, Vermont
    Rupert, Vermont is a small rural town in southwestern Vermont known for its scenic Green Mountain setting and historic New England character.
  • E. Middlesex, Vermont
    Middlesex, Vermont is a small rural town in central Vermont known for its scenic landscape, outdoor recreation, and proximity to the state capital, Montpelier.
  • 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_69b345506b408190b0e3dee616738a7d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b352adce588190b9e6ed53458aa1e1 completed March 12, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6135ecdc08190b2a7458614cf4c54 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:20 p.m.