Triple

T28093181
Position Surface form Disambiguated ID Type / Status
Subject Richfield, Utah E710010 entity
Predicate hasAirport P105 FINISHED
Object Richfield Municipal Airport
Richfield Municipal Airport is a public-use airport serving general aviation needs for the city of Richfield and the surrounding region in central Utah.
E1849395 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: Richfield Municipal Airport | Statement: [Richfield, Utah, hasAirport, Richfield Municipal Airport]
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: Richfield Municipal Airport
Triple: [Richfield, Utah, hasAirport, Richfield Municipal Airport]
Generated description
Richfield Municipal Airport is a public-use airport serving general aviation needs for the city of Richfield and the surrounding region in central Utah.

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_69ef9b70fd108190a875953b2e50ca91 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6406bdeb08190b36abe9936f82d7c completed May 2, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25378393d88190872b44aec56f5300 completed June 7, 2026, 9:18 a.m.
NEDg Description generation batch_6a253b7b6e1081908bb2790e3effce40 completed June 7, 2026, 9:35 a.m.
NED2 Entity disambiguation (via description) batch_6a253f72bf4c8190846d42f2373f400f completed June 7, 2026, 9:52 a.m.
Created at: April 27, 2026, 8:59 p.m.