Triple

T31537192
Position Surface form Disambiguated ID Type / Status
Subject Burke, Vermont E804638 entity
Predicate hasVillage P4011 FINISHED
Object West Burke, Vermont
West Burke, Vermont is a small village in Caledonia County known for its rural New England character and proximity to outdoor recreation in Vermont’s Northeast Kingdom.
E804638 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: West Burke, Vermont | Statement: [Burke, Vermont, hasVillage, West Burke, Vermont]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: West Burke, Vermont
Triple: [Burke, Vermont, hasVillage, West Burke, Vermont]
Generated description
West Burke, Vermont is a small village in Caledonia County known for its rural New England character and proximity to outdoor recreation in Vermont’s Northeast Kingdom.

Provenance (5 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_69f348d03ef88190a2b73d7b94b9e02d completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a78300c0819099abfce061b000c9 completed May 3, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b562e557c819089e812c8982129c4 completed June 12, 2026, 12:43 a.m.
NEDg Description generation batch_6a2b576541208190a52a5eaecf8962c8 completed June 12, 2026, 12:48 a.m.
NED2 Entity disambiguation (via description) batch_6a2b601da44481908fca8a5331ba5b38 completed June 12, 2026, 1:25 a.m.
Created at: April 30, 2026, 10:04 p.m.