Triple

T12745206
Position Surface form Disambiguated ID Type / Status
Subject Bognor Regis railway station E304585 entity
Predicate stationCode P1289 FINISHED
Object BOG
BOG is the three-letter National Rail station code for Bognor Regis railway station in West Sussex, England.
 E999107 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: BOG | Statement: [Bognor Regis railway station, stationCode, BOG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BOG
Context triple: [Bognor Regis railway station, stationCode, BOG]
  • A. BOG
    BOG is the vehicle registration code used for motor vehicles registered in the Capital District of Bogotá, Colombia.
  • B. BOG
    BOG is the IATA airport code for El Dorado International Airport, the main international gateway serving Bogotá, Colombia.
  • C. BOG
    BOG is the commonly used acronym for the Florida Board of Governors, the governing body overseeing the State University System of Florida.
  • D. BOH
    BOH is the three-letter IATA airport code for Bournemouth Airport in southern England.
  • E. BO
    BO is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Bolivia in international standards and systems.
  • 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: BOG
Triple: [Bognor Regis railway station, stationCode, BOG]
Generated description
BOG is the three-letter National Rail station code for Bognor Regis railway station in West Sussex, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BOG
Target entity description: BOG is the three-letter National Rail station code for Bognor Regis railway station in West Sussex, England.
  • A. BOG
    BOG is the IATA airport code for El Dorado International Airport, the main international gateway serving Bogotá, Colombia.
  • B. BOG
    BOG is the vehicle registration code used for motor vehicles registered in the Capital District of Bogotá, Colombia.
  • C. BOG
    BOG is the commonly used acronym for the Florida Board of Governors, the governing body overseeing the State University System of Florida.
  • D. BOH
    BOH is the three-letter IATA airport code for Bournemouth Airport in southern England.
  • E. BO
    BO is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Bolivia in international standards and systems.
  • 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96bd42fe08190a85467b1a998d2af completed April 10, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c94265481908ace9cac757df890 completed May 2, 2026, 10:37 p.m.
NEDg Description generation batch_69f67d897c6881908d73eb2923e55938 completed May 2, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_69f67de628588190978f30972d5ce13a completed May 2, 2026, 10:42 p.m.
Created at: April 9, 2026, 5:26 p.m.