Triple

T8462894
Position Surface form Disambiguated ID Type / Status
Subject Banbury railway station E200086 entity
Predicate hasStationCode P1289 FINISHED
Object BAN
BAN is the National Rail station code for Banbury railway station in Oxfordshire, England.
 E736018 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: BAN | Statement: [Banbury railway station, hasStationCode, BAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BAN
Context triple: [Banbury railway station, hasStationCode, BAN]
  • A. Ban
    Ban was the nickname of Ban Johnson, the influential early 20th-century baseball executive who served as the first president of the American League.
  • B. Banning
    Banning is a small city in Southern California known for its location along the I-10 corridor between Los Angeles and Palm Springs.
  • C. BANZSL
    BANZSL is the family of closely related sign languages used in Britain, Australia, and New Zealand, sharing a common historical origin and many linguistic features.
  • D. BAL
    BAL is the commonly used acronym for the Basketball Africa League, a professional pan-African basketball competition organized in partnership with the NBA and FIBA.
  • E. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • 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: BAN
Triple: [Banbury railway station, hasStationCode, BAN]
Generated description
BAN is the National Rail station code for Banbury railway station in Oxfordshire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BAN
Target entity description: BAN is the National Rail station code for Banbury railway station in Oxfordshire, England.
  • A. Ban
    Ban was the nickname of Ban Johnson, the influential early 20th-century baseball executive who served as the first president of the American League.
  • B. Banning
    Banning is a small city in Southern California known for its location along the I-10 corridor between Los Angeles and Palm Springs.
  • C. BANZSL
    BANZSL is the family of closely related sign languages used in Britain, Australia, and New Zealand, sharing a common historical origin and many linguistic features.
  • D. BAL
    BAL is the commonly used acronym for the Basketball Africa League, a professional pan-African basketball competition organized in partnership with the NBA and FIBA.
  • E. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • 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_69ca83198c4c8190a337bf717d1813f5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe4a251f08190840a7fc31ff528b5 completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce39d5f50081908e273d5286a0d397 completed April 2, 2026, 9:41 a.m.
NEDg Description generation batch_69ce3bf7d2748190ad7ca0649fe2cb0f completed April 2, 2026, 9:50 a.m.
NED2 Entity disambiguation (via description) batch_69ce3c8aac8c8190a81c2c51cd0c06e0 completed April 2, 2026, 9:53 a.m.
Created at: March 30, 2026, 6:10 p.m.