Triple

T37265176
Position Surface form Disambiguated ID Type / Status
Subject Town of Ellicott E924361 entity
Predicate hasCommunity P2605 FINISHED
Object West Ellicott, New York
West Ellicott, New York is a suburban community in Chautauqua County that serves as a residential and commercial area just outside the city of Jamestown.
E2221034 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 Ellicott, New York | Statement: [Town of Ellicott, hasCommunity, West Ellicott, New York]
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 Ellicott, New York
Triple: [Town of Ellicott, hasCommunity, West Ellicott, New York]
Generated description
West Ellicott, New York is a suburban community in Chautauqua County that serves as a residential and commercial area just outside the city of Jamestown.

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_69f76eabd6c481909d414a80a1345c98 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb375b5b2c819098e22c76c0ba166f completed May 6, 2026, 12:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40512cc8d08190beb1f70bbace8d79 completed June 27, 2026, 10:39 p.m.
NEDg Description generation batch_6a40524ea5e48190905a1475417546a7 completed June 27, 2026, 10:44 p.m.
NED2 Entity disambiguation (via description) batch_6a4052c3ada481908d4ffbfaad34c24b completed June 27, 2026, 10:46 p.m.
Created at: May 3, 2026, 4:15 p.m.