Triple

T37252241
Position Surface form Disambiguated ID Type / Status
Subject Lincoln Parish E924024 entity
Predicate hasAirport P105 FINISHED
Object Ruston Regional Airport
Ruston Regional Airport is a public airport serving the city of Ruston and the surrounding Lincoln Parish area in Louisiana, providing facilities for general aviation and regional air services.
E2219339 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: Ruston Regional Airport | Statement: [Lincoln Parish, hasAirport, Ruston Regional 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: Ruston Regional Airport
Triple: [Lincoln Parish, hasAirport, Ruston Regional Airport]
Generated description
Ruston Regional Airport is a public airport serving the city of Ruston and the surrounding Lincoln Parish area in Louisiana, providing facilities for general aviation and regional air services.

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_69f76eaabb4c819093b751b139dad551 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb37008ce48190a410a10f543d5088 completed May 6, 2026, 12:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043d1a9888190a9c17142b917f37e completed June 27, 2026, 9:42 p.m.
NEDg Description generation batch_6a4044fd17208190b590493419679ef1 completed June 27, 2026, 9:47 p.m.
NED2 Entity disambiguation (via description) batch_6a4046ed8adc81909bb53bad47859232 completed June 27, 2026, 9:55 p.m.
Created at: May 3, 2026, 4:15 p.m.