Triple

T15671819
Position Surface form Disambiguated ID Type / Status
Subject Bergen op Zoom railway station E377331 entity
Predicate hasStationCode P1289 FINISHED
Object Bgn
Bgn is the official station code used to identify Bergen op Zoom railway station in the Netherlands.
E1169598 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: Bgn | Statement: [Bergen op Zoom railway station, hasStationCode, Bgn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bgn
Context triple: [Bergen op Zoom railway station, hasStationCode, Bgn]
  • A. BGN
    BGN is the official currency code for the Bulgarian lev, the national currency of Bulgaria.
  • B. BGN
    BGN is the standard abbreviation for the U.S. Board on Geographic Names, the federal body that maintains uniform geographic name usage across the United States government.
  • C. BGN
    BGN is the National Rail station code for Bridgend railway station in South Wales, United Kingdom.
  • D. B.G.
    B.G. is an American rapper from New Orleans, best known as a former member of the Hot Boys and an early standout artist on the Cash Money Records label.
  • E. BG
    BG is the vehicle registration code used for Belgrade, the capital city of Serbia.
  • 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: Bgn
Triple: [Bergen op Zoom railway station, hasStationCode, Bgn]
Generated description
Bgn is the official station code used to identify Bergen op Zoom railway station in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bgn
Target entity description: Bgn is the official station code used to identify Bergen op Zoom railway station in the Netherlands.
  • A. BGN
    BGN is the official currency code for the Bulgarian lev, the national currency of Bulgaria.
  • B. BGN
    BGN is the standard abbreviation for the U.S. Board on Geographic Names, the federal body that maintains uniform geographic name usage across the United States government.
  • C. BGN
    BGN is the National Rail station code for Bridgend railway station in South Wales, United Kingdom.
  • D. B.G.
    B.G. is an American rapper from New Orleans, best known as a former member of the Hot Boys and an early standout artist on the Cash Money Records label.
  • E. BG
    BG is the vehicle registration code used for Belgrade, the capital city of Serbia.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f13b1b08190beabc9f4098aa096 completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff67a540a88190b2460ff1d99767ac completed May 9, 2026, 4:58 p.m.
NEDg Description generation batch_69ff68395718819098571f2c18b2276e completed May 9, 2026, 5 p.m.
NED2 Entity disambiguation (via description) batch_69ff6897aebc8190a4f2a5e9866a3f74 completed May 9, 2026, 5:02 p.m.
Created at: April 10, 2026, 4:16 a.m.