Triple

T35383265
Position Surface form Disambiguated ID Type / Status
Subject Aliquippa School District E1022712 entity
Predicate operates P24 FINISHED
Object Aliquippa Elementary School
Aliquippa Elementary School is a public primary school in Aliquippa, Pennsylvania, serving early-grade students in the Aliquippa School District.
E2141645 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: Aliquippa Elementary School | Statement: [Aliquippa School District, operates, Aliquippa Elementary 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: Aliquippa Elementary School
Triple: [Aliquippa School District, operates, Aliquippa Elementary School]
Generated description
Aliquippa Elementary School is a public primary school in Aliquippa, Pennsylvania, serving early-grade students in the Aliquippa School District.

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_69f76df28d8c819089f2c5799fe7d079 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f794f24e588190965e39b77534d53f completed May 3, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a384022ee5081909dc89294eb8cfb17 completed June 21, 2026, 7:48 p.m.
NEDg Description generation batch_6a3840adcad081908294292104447b0c completed June 21, 2026, 7:51 p.m.
NED2 Entity disambiguation (via description) batch_6a38411c749881908ea838276aeed039 completed June 21, 2026, 7:53 p.m.
Created at: May 3, 2026, 4:03 p.m.