Triple

T26677406
Position Surface form Disambiguated ID Type / Status
Subject No. 158 Squadron RAF E672499 entity
Predicate garrison P75 FINISHED
Object RAF Rufforth
RAF Rufforth was a Royal Air Force station in North Yorkshire, England, used primarily as a World War II bomber airfield.
E1803849 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: RAF Rufforth | Statement: [No. 158 Squadron RAF, garrison, RAF Rufforth]
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: RAF Rufforth
Triple: [No. 158 Squadron RAF, garrison, RAF Rufforth]
Generated description
RAF Rufforth was a Royal Air Force station in North Yorkshire, England, used primarily as a World War II bomber airfield.

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_69eecda13424819092b17942c4edf722 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f617053a8081908c4b413a38c84e41 completed May 2, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c8d3bf0c8190a1e6c299f65fb1be completed May 26, 2026, 4:22 p.m.
NEDg Description generation batch_6a15ca33a1108190895682956756c2f1 completed May 26, 2026, 4:28 p.m.
NED2 Entity disambiguation (via description) batch_6a15caa74e9c8190ad43be1d8ed6ad15 completed May 26, 2026, 4:30 p.m.
Created at: April 27, 2026, 3:17 a.m.