Triple

T27383921
Position Surface form Disambiguated ID Type / Status
Subject Clinton County, Ohio E691312 entity
Predicate hasMajorHighway P385 FINISHED
Object State Route 72
State Route 72 is a north–south state highway in southwestern Ohio that connects several rural communities and small towns, including areas within Clinton County.
 E2293678 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: State Route 72 | Statement: [Clinton County, Ohio, hasMajorHighway, State Route 72]
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: State Route 72
Triple: [Clinton County, Ohio, hasMajorHighway, State Route 72]
Generated description
State Route 72 is a north–south state highway in southwestern Ohio that connects several rural communities and small towns, including areas within Clinton County.

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_69ef520386788190bc92cfcd97ebb67a completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62c89b7b88190a8b2af842f5f9cca completed May 2, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7af02e29488190bad8ff1a966cb042 completed Aug. 11, 2026, 9:49 a.m.
NEDg Description generation batch_6a7af093e43081908a1ed93ffea4620a completed Aug. 11, 2026, 9:51 a.m.
NED2 Entity disambiguation (via description) batch_6a7af100e31c8190bde42e0cd9442381 completed Aug. 11, 2026, 9:53 a.m.
Created at: April 27, 2026, 12:23 p.m.