Triple

T27386039
Position Surface form Disambiguated ID Type / Status
Subject Toquerville, Utah E691375 entity
Predicate locatedNear P294 FINISHED
Object State Route 17
State Route 17 is a short state highway in southwestern Utah that serves as a connector between Interstate 15 and State Route 9, providing access toward Zion National Park.
 E2293736 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 17 | Statement: [Toquerville, Utah, locatedNear, State Route 17]
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 17
Triple: [Toquerville, Utah, locatedNear, State Route 17]
Generated description
State Route 17 is a short state highway in southwestern Utah that serves as a connector between Interstate 15 and State Route 9, providing access toward Zion National Park.

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_69f62c8af8508190bf5e40515d5d8f34 completed May 2, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7af84d317c8190b9db2b990a5e101c completed Aug. 11, 2026, 10:24 a.m.
NEDg Description generation batch_6a7af8fb465881908d50b11971994f1d completed Aug. 11, 2026, 10:27 a.m.
NED2 Entity disambiguation (via description) batch_6a7af94dd3908190bb5a9bbe2cca1a0e completed Aug. 11, 2026, 10:28 a.m.
Created at: April 27, 2026, 12:24 p.m.