Triple

T7780671
Position Surface form Disambiguated ID Type / Status
Subject Leicester, Massachusetts E221506 entity
Predicate hasVillage P4011 FINISHED
Object Greenville, Massachusetts
Greenville, Massachusetts is a small village within the town of Leicester in Worcester County, known as a residential community in central Massachusetts.
E2295161 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: Greenville, Massachusetts | Statement: [Leicester, Massachusetts, hasVillage, Greenville, Massachusetts]
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: Greenville, Massachusetts
Triple: [Leicester, Massachusetts, hasVillage, Greenville, Massachusetts]
Generated description
Greenville, Massachusetts is a small village within the town of Leicester in Worcester County, known as a residential community in central Massachusetts.

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_69ca83ebbef881909ac47f789145fef7 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69caa4d6cf9881909f5220437db13cc7 completed March 30, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7d104d03588190adaaa1f0a3687d1f completed Aug. 13, 2026, 12:31 a.m.
NEDg Description generation batch_6a7d10b3b014819099710f82c31887cb completed Aug. 13, 2026, 12:32 a.m.
NED2 Entity disambiguation (via description) batch_6a7d1184367c8190bb6b688de8b5ec8b completed Aug. 13, 2026, 12:36 a.m.
Created at: March 30, 2026, 4:20 p.m.