Triple

T25578722
Position Surface form Disambiguated ID Type / Status
Subject Bridgewater-Raritan Regional School District E641180 entity
Predicate operatesSchool P226 FINISHED
Object Crim Primary School
Crim Primary School is an elementary school serving young students in the Bridgewater-Raritan area of New Jersey.
E1688391 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: Crim Primary School | Statement: [Bridgewater-Raritan Regional School District, operatesSchool, Crim Primary School]
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: Crim Primary School
Triple: [Bridgewater-Raritan Regional School District, operatesSchool, Crim Primary School]
Generated description
Crim Primary School is an elementary school serving young students in the Bridgewater-Raritan area of New Jersey.

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_69e75dc281bc819095ec04dc0c3a94d0 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f9329b8c819088fd2a63492c5c5a completed May 2, 2026, 1:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b761746881909bb71492956c9a68 completed May 22, 2026, 8:06 p.m.
NEDg Description generation batch_6a10b94377108190a5fb35e99b5f0351 completed May 22, 2026, 8:14 p.m.
NED2 Entity disambiguation (via description) batch_6a10b9c6dbf48190abe4efb4035db2a0 completed May 22, 2026, 8:17 p.m.
Created at: April 21, 2026, 4:03 p.m.