Triple

T27002144
Position Surface form Disambiguated ID Type / Status
Subject Elkhorn, Nebraska E680138 entity
Predicate schoolDistrict P226 FINISHED
Object Elkhorn Public Schools
Elkhorn Public Schools is a public school district serving the community of Elkhorn and surrounding areas in the Omaha metropolitan region of Nebraska.
E1755023 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: Elkhorn Public Schools | Statement: [Elkhorn, Nebraska, schoolDistrict, Elkhorn Public Schools]
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: Elkhorn Public Schools
Triple: [Elkhorn, Nebraska, schoolDistrict, Elkhorn Public Schools]
Generated description
Elkhorn Public Schools is a public school district serving the community of Elkhorn and surrounding areas in the Omaha metropolitan region of Nebraska.

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_69eeeb52908c8190bd246244686aa455 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f621ceaaf481908b1b31f01591a427 completed May 2, 2026, 4:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123ab2121c8190a9d351ad0ed13317 completed May 23, 2026, 11:39 p.m.
NEDg Description generation batch_6a123ba9aea081909f20ff78ab91747e completed May 23, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a123c4f67388190a885b5ce89f9baa6 completed May 23, 2026, 11:46 p.m.
Created at: April 27, 2026, 6:58 a.m.