Triple

T13664858
Position Surface form Disambiguated ID Type / Status
Subject central Vermont E327090 entity
Predicate contains P35 FINISHED
Object Orange, Vermont E226326 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: Orange, Vermont | Statement: [central Vermont, contains, Orange, Vermont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orange, Vermont
Context triple: [central Vermont, contains, Orange, Vermont]
  • A. Orange, Vermont chosen
    Orange, Vermont is a small rural town in central Vermont known for its scenic landscape and quiet, close-knit community.
  • B. Orwell, Vermont
    Orwell, Vermont is a small rural town in southwestern Vermont known for its agricultural landscape and historic New England character.
  • C. Orange, New Hampshire
    Orange, New Hampshire is a small rural town in Grafton County known for its mountainous terrain and proximity to Mount Cardigan.
  • D. 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.
  • E. Walden, Vermont
    Walden, Vermont is a small rural town located in northeastern Vermont within Caledonia County, known for its scenic landscapes and quiet, agricultural character.
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc622a07c81909ef7fb55e719dd9a completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff1330527481908d518093debc9ad1 completed May 9, 2026, 10:57 a.m.
Created at: April 9, 2026, 9:52 p.m.