Triple

T13412472
Position Surface form Disambiguated ID Type / Status
Subject RAF Uxbridge E320122 entity
Predicate stationCode P1289 FINISHED
Object UX
UX is the station code for RAF Uxbridge, a former Royal Air Force station in Uxbridge, west London, historically significant for its role in the Battle of Britain.
E1038880 NE FINISHED

How this triple was built (4 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: UX | Statement: [RAF Uxbridge, stationCode, UX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UX
Context triple: [RAF Uxbridge, stationCode, UX]
  • A. UX
    UX is the two-letter IATA airline designator assigned to the Spanish carrier Air Europa.
  • B. UI
    UI is the commonly used abbreviation for the University of Indonesia, one of the country’s leading public universities.
  • C. UI
    UI is the commonly used abbreviation for the University of Iceland, the country’s leading public research university located in Reykjavík.
  • D. UIS
    UIS is a public university in Springfield, Illinois, known for its liberal arts and professional programs within the University of Illinois system.
  • E. UIS
    UIS is the stock ticker symbol for Unisys Corporation, an American global information technology services and solutions company.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: UX
Triple: [RAF Uxbridge, stationCode, UX]
Generated description
UX is the station code for RAF Uxbridge, a former Royal Air Force station in Uxbridge, west London, historically significant for its role in the Battle of Britain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: UX
Target entity description: UX is the station code for RAF Uxbridge, a former Royal Air Force station in Uxbridge, west London, historically significant for its role in the Battle of Britain.
  • A. UX
    UX is the two-letter IATA airline designator assigned to the Spanish carrier Air Europa.
  • B. UI
    UI is the commonly used abbreviation for the University of Iceland, the country’s leading public research university located in Reykjavík.
  • C. UI
    UI is the commonly used abbreviation for the University of Indonesia, one of the country’s leading public universities.
  • D. UIS
    UIS is a public university in Springfield, Illinois, known for its liberal arts and professional programs within the University of Illinois system.
  • E. UIS
    UIS is the stock ticker symbol for Unisys Corporation, an American global information technology services and solutions company.
  • F. None of above. chosen

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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb556948190af008c88e5bbf051 completed April 12, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7307e9b5881908eb2cd9e4fa7c5f2 completed May 3, 2026, 11:24 a.m.
NEDg Description generation batch_69f73195e4d88190ad356d0e3e18d34f completed May 3, 2026, 11:29 a.m.
NED2 Entity disambiguation (via description) batch_69f73220ffc08190bfb1b89757efd606 completed May 3, 2026, 11:31 a.m.
Created at: April 9, 2026, 9:35 p.m.