Triple

T30561779
Position Surface form Disambiguated ID Type / Status
Subject Crane, Oregon E777863 entity
Predicate schoolDistrict P226 FINISHED
Object Crane Elementary School District
Crane Elementary School District is a public school district serving elementary-level students in the rural community of Crane, Oregon.
E1922247 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: Crane Elementary School District | Statement: [Crane, Oregon, schoolDistrict, Crane Elementary School District]
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: Crane Elementary School District
Triple: [Crane, Oregon, schoolDistrict, Crane Elementary School District]
Generated description
Crane Elementary School District is a public school district serving elementary-level students in the rural community of Crane, Oregon.

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_69f2249ed41c8190b175170ecfd6e1c5 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f688d92b748190a69e5b66ace513be completed May 2, 2026, 11:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2870da88a881908b65ddd95e39645f completed June 9, 2026, 8 p.m.
NEDg Description generation batch_6a2871dae4348190ae0c3b915ab12070 completed June 9, 2026, 8:04 p.m.
NED2 Entity disambiguation (via description) batch_6a2872cdc6948190ab2904f009993934 completed June 9, 2026, 8:08 p.m.
Created at: April 29, 2026, 8:21 p.m.