Triple

T26002136
Position Surface form Disambiguated ID Type / Status
Subject Orangeville, Illinois E646657 entity
Predicate hasPublicSchool P113 FINISHED
Object Orangeville Elementary School
Orangeville Elementary School is a public primary school serving the early-grade educational needs of children in the village of Orangeville, Illinois.
E1707368 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: Orangeville Elementary School | Statement: [Orangeville, Illinois, hasPublicSchool, Orangeville 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: Orangeville Elementary School
Triple: [Orangeville, Illinois, hasPublicSchool, Orangeville Elementary School]
Generated description
Orangeville Elementary School is a public primary school serving the early-grade educational needs of children in the village of Orangeville, Illinois.

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_69e77e89d5848190b54352cdb74f6029 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f605770b2481908c1674952889f62f completed May 2, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111b0d5e04819085ac6e8101fb9153 completed May 23, 2026, 3:12 a.m.
NEDg Description generation batch_6a111bd7e1188190b3275dc1efe4bfb3 completed May 23, 2026, 3:15 a.m.
NED2 Entity disambiguation (via description) batch_6a111cbb1ed88190a4980f8fc8a0a19f completed May 23, 2026, 3:19 a.m.
Created at: April 22, 2026, 9 a.m.