Triple

T35939231
Position Surface form Disambiguated ID Type / Status
Subject Prince George Airport E1039392 entity
Predicate formerName P65 FINISHED
Object Prince George Aerodrome
Prince George Aerodrome was the original airfield serving Prince George, British Columbia, before its expansion and modernization into the present-day Prince George Airport.
E2163869 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: Prince George Aerodrome | Statement: [Prince George Airport, formerName, Prince George Aerodrome]
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: Prince George Aerodrome
Triple: [Prince George Airport, formerName, Prince George Aerodrome]
Generated description
Prince George Aerodrome was the original airfield serving Prince George, British Columbia, before its expansion and modernization into the present-day Prince George Airport.

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_69f76e24bbd0819096b837d35371639a completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7abad3fa48190a668f4f4faa61f25 completed May 3, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38b6f9c05c8190831e2a4ca65d0dbf completed June 22, 2026, 4:15 a.m.
NEDg Description generation batch_6a38b7d8c5fc8190a7cce91a93d1b905 completed June 22, 2026, 4:19 a.m.
NED2 Entity disambiguation (via description) batch_6a38b86a90b48190810a306e1cf50744 completed June 22, 2026, 4:22 a.m.
Created at: May 3, 2026, 4:07 p.m.