Triple

T31436903
Position Surface form Disambiguated ID Type / Status
Subject Oak Harbor, Ohio E801958 entity
Predicate hasTransportation P105 FINISHED
Object State Route 105
State Route 105 is a state highway in Ohio that serves as a key local connector route in and around the Oak Harbor area.
 E2295734 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 105 | Statement: [Oak Harbor, Ohio, hasTransportation, State Route 105]
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 105
Triple: [Oak Harbor, Ohio, hasTransportation, State Route 105]
Generated description
State Route 105 is a state highway in Ohio that serves as a key local connector route in and around the Oak Harbor area.

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_69f348c475348190bf579ca858eec77c completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a0edeaf4819080a45f1bcbbffd0e completed May 3, 2026, 1:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a81e88ac8f881908e13183f18ce16ee completed Aug. 16, 2026, 4:42 p.m.
NEDg Description generation batch_6a81e8e58e8c8190be9090e9e36e7e2d completed Aug. 16, 2026, 4:44 p.m.
NED2 Entity disambiguation (via description) batch_6a81e9379f408190a19b00a909c265b3 completed Aug. 16, 2026, 4:45 p.m.
Created at: April 30, 2026, 9:02 p.m.