Triple

T26627539
Position Surface form Disambiguated ID Type / Status
Subject Nevada State Route 267 E668396 entity
Predicate formerName P65 FINISHED
Object State Route 72
State Route 72 was the former designation for what is now Nevada State Route 267, a highway in Nevada.
 E2292944 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: [Nevada State Route 267, formerName, 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: [Nevada State Route 267, formerName, State Route 72]
Generated description
State Route 72 was the former designation for what is now Nevada State Route 267, a highway in Nevada.

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_69ee9cff507c819092b95bf7219a702e completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f615ea59048190880a13cb9a9f8126 completed May 2, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a462a19c48190ae670af83a848fd2 completed Aug. 10, 2026, 9:44 p.m.
NEDg Description generation batch_6a7a468f53d48190b323d015163a8b1a completed Aug. 10, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_6a7a46d559c081908403be07a44fded8 completed Aug. 10, 2026, 9:47 p.m.
Created at: April 27, 2026, 2:23 a.m.