Triple

T23607385
Position Surface form Disambiguated ID Type / Status
Subject Greeley, Colorado, United States E582933 entity
Predicate majorHighway P385 FINISHED
Object State Highway 257
State Highway 257 is a Colorado state highway that serves as a key regional connector route in and around Greeley in northern Colorado.
 E2295492 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 Highway 257 | Statement: [Greeley, Colorado, United States, majorHighway, State Highway 257]
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 Highway 257
Triple: [Greeley, Colorado, United States, majorHighway, State Highway 257]
Generated description
State Highway 257 is a Colorado state highway that serves as a key regional connector route in and around Greeley in northern Colorado.

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_69e248faa2788190abb1581742daa6aa completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b0f107048190b81eade6a50db2da completed April 29, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7d61f889c48190b32facf284d73b86 completed Aug. 13, 2026, 6:19 a.m.
NEDg Description generation batch_6a7d624dc67481909d03c55e28ca6484 completed Aug. 13, 2026, 6:21 a.m.
NED2 Entity disambiguation (via description) batch_6a7d62ea80588190a782c4d64e52c8d2 completed Aug. 13, 2026, 6:23 a.m.
Created at: April 17, 2026, 6:44 p.m.