Triple

T8945051
Position Surface form Disambiguated ID Type / Status
Subject Burnley Central railway station E213200 entity
Predicate stationCode P1289 FINISHED
Object BNC
BNC is the three-letter National Rail station code for Burnley Central railway station in Lancashire, England.
 E767964 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: BNC | Statement: [Burnley Central railway station, stationCode, BNC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BNC
Context triple: [Burnley Central railway station, stationCode, BNC]
  • A. BNC
    BNC is the IATA airport code for Beni Airport in the Democratic Republic of the Congo.
  • B. BNC
    BNC is the commonly used abbreviation for Brasenose College, one of the constituent colleges of the University of Oxford.
  • C. BN2
    BN2 is a UK postal district covering parts of eastern Brighton and nearby areas within the BN (Brighton) postcode region.
  • D. BnG
    BnG is the commonly used abbreviation for Bòrd na Gàidhlig, the principal public body responsible for promoting and supporting the Scottish Gaelic language in Scotland.
  • E. BN
    BN is the vehicle registration code used on license plates for the German city of Bonn.
  • 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: BNC
Triple: [Burnley Central railway station, stationCode, BNC]
Generated description
BNC is the three-letter National Rail station code for Burnley Central railway station in Lancashire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BNC
Target entity description: BNC is the three-letter National Rail station code for Burnley Central railway station in Lancashire, England.
  • A. BNC
    BNC is the commonly used abbreviation for Brasenose College, one of the constituent colleges of the University of Oxford.
  • B. BNC
    BNC is the IATA airport code for Beni Airport in the Democratic Republic of the Congo.
  • C. BN2
    BN2 is a UK postal district covering parts of eastern Brighton and nearby areas within the BN (Brighton) postcode region.
  • D. BnG
    BnG is the commonly used abbreviation for Bòrd na Gàidhlig, the principal public body responsible for promoting and supporting the Scottish Gaelic language in Scotland.
  • E. BN
    BN is the vehicle registration code used on license plates for the German city of Bonn.
  • 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_69ca839843408190a39069a029a89f15 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66db998c8190999a7a686bbdda1f completed April 1, 2026, 12:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc1fcb44481908324220aeba1f4e2 completed April 3, 2026, 1:34 p.m.
NEDg Description generation batch_69cfc31798ec81908c200dd17be5e785 completed April 3, 2026, 1:39 p.m.
NED2 Entity disambiguation (via description) batch_69cfc44441208190a6b588c0609511fb completed April 3, 2026, 1:44 p.m.
Created at: March 30, 2026, 6:59 p.m.