Triple

T31771610
Position Surface form Disambiguated ID Type / Status
Subject Hinckley Township E810953 entity
Predicate hasSchoolDistrict P226 FINISHED
Object Highland Local School District
Highland Local School District is a public school system serving students in and around Hinckley Township in northeastern Ohio.
E1978892 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: Highland Local School District | Statement: [Hinckley Township, hasSchoolDistrict, Highland Local 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: Highland Local School District
Triple: [Hinckley Township, hasSchoolDistrict, Highland Local School District]
Generated description
Highland Local School District is a public school system serving students in and around Hinckley Township in northeastern Ohio.

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_69f348e463e08190b902d4819195e1f0 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6abaff7648190a488163179a28fc2 completed May 3, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2d9d5058a48190b21b7ff16fb16c3a completed June 13, 2026, 6:11 p.m.
NEDg Description generation batch_6a2da156d36881909e75b80ac64ef91d completed June 13, 2026, 6:28 p.m.
NED2 Entity disambiguation (via description) batch_6a2e573855248190adf132c8fb9dfeb6 completed June 14, 2026, 7:24 a.m.
Created at: April 30, 2026, 11:33 p.m.