Triple

T31019223
Position Surface form Disambiguated ID Type / Status
Subject Utah state roads E790406 entity
Predicate hasComponent P35 FINISHED
Object Utah State Route 62
Utah State Route 62 is a state highway in south-central Utah that connects the town of Junction with the Otter Creek Reservoir area, passing through rural Sevier and Piute counties.
 E1982039 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: Utah State Route 62 | Statement: [Utah state roads, hasComponent, Utah State Route 62]
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: Utah State Route 62
Triple: [Utah state roads, hasComponent, Utah State Route 62]
Generated description
Utah State Route 62 is a state highway in south-central Utah that connects the town of Junction with the Otter Creek Reservoir area, passing through rural Sevier and Piute counties.

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_69f224c811508190a7de096a5b1f5798 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6948dcf6081909a7219c73534dc11 completed May 3, 2026, 12:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e7fb939a08190bc7bb4850999cd27 completed June 14, 2026, 10:17 a.m.
NEDg Description generation batch_6a2e80a633308190a46794c5d992993c completed June 14, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2e817feee48190a55b72e9901e1ba6 completed June 14, 2026, 10:25 a.m.
Created at: April 29, 2026, 8:58 p.m.