Triple

T29095440
Position Surface form Disambiguated ID Type / Status
Subject Town of Warwick E734985 entity
Predicate contains P35 FINISHED
Object hamlet of Amity, New York
The hamlet of Amity, New York is a small rural community within Orange County known for its quiet residential character and proximity to the larger town centers of Warwick.
E1851738 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: hamlet of Amity, New York | Statement: [Town of Warwick, contains, hamlet of Amity, 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: hamlet of Amity, New York
Triple: [Town of Warwick, contains, hamlet of Amity, New York]
Generated description
The hamlet of Amity, New York is a small rural community within Orange County known for its quiet residential character and proximity to the larger town centers of Warwick.

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_69f05b0ed66481908f2e864fa550d2f1 completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f6618069888190aa87dd09a751a2c2 completed May 2, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2537b4ec788190ba7b9a7d3ecbbffc completed June 7, 2026, 9:19 a.m.
NEDg Description generation batch_6a253bf87598819087116abf2274d649 completed June 7, 2026, 9:38 a.m.
NED2 Entity disambiguation (via description) batch_6a25470a98f48190b7afa02e39675cc3 completed June 7, 2026, 10:25 a.m.
Created at: April 28, 2026, 11:08 a.m.