Triple

T27832686
Position Surface form Disambiguated ID Type / Status
Subject Idaho highway system E703145 entity
Predicate includes P1393 FINISHED
Object U.S. Route 89 in Idaho
U.S. Route 89 in Idaho is a north–south U.S. Highway that briefly traverses the southeastern corner of the state, connecting Utah to Wyoming through scenic rural and mountainous terrain.
E1792677 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: U.S. Route 89 in Idaho | Statement: [Idaho highway system, includes, U.S. Route 89 in Idaho]
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: U.S. Route 89 in Idaho
Triple: [Idaho highway system, includes, U.S. Route 89 in Idaho]
Generated description
U.S. Route 89 in Idaho is a north–south U.S. Highway that briefly traverses the southeastern corner of the state, connecting Utah to Wyoming through scenic rural and mountainous terrain.

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_69ef840b94b08190950a4f77296938b2 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6389cf96c8190a045e3c53f83f3cd completed May 2, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f72ebea88190a73e6a1086d00faf completed May 24, 2026, 1:03 p.m.
NEDg Description generation batch_6a12fb4a4a808190bc0821b2bc754da0 completed May 24, 2026, 1:21 p.m.
NED2 Entity disambiguation (via description) batch_6a12fd21fb2c8190b52459bd901c05a0 completed May 24, 2026, 1:29 p.m.
Created at: April 27, 2026, 5:57 p.m.