Triple

T15628757
Position Surface form Disambiguated ID Type / Status
Subject Birkenhead Central railway station E375752 entity
Predicate stationCode P1289 FINISHED
Object BKC
BKC is the National Rail station code for Birkenhead Central railway station in Merseyside, England.
 E1167564 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: BKC | Statement: [Birkenhead Central railway station, stationCode, BKC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BKC
Context triple: [Birkenhead Central railway station, stationCode, BKC]
  • A. BKC
    BKC is the commonly used abbreviation for Ritsumeikan University's Biwako-Kusatsu Campus in Shiga Prefecture, Japan.
  • B. RBKC
    RBKC is the commonly used abbreviation for the Royal Borough of Kensington and Chelsea, a central London local authority area known for its affluent neighborhoods and cultural landmarks.
  • C. Kannai business district
    Kannai business district is a central commercial and administrative area of Yokohama known for its government offices, corporate buildings, and historic urban streetscape.
  • D. BKH
    BKH is the National Rail station code for Blackheath railway station in southeast London, England.
  • E. Kappabashi
    Kappabashi is a famous Tokyo shopping street and district known for its many stores specializing in kitchenware, restaurant supplies, and realistic plastic food models.
  • 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: BKC
Triple: [Birkenhead Central railway station, stationCode, BKC]
Generated description
BKC is the National Rail station code for Birkenhead Central railway station in Merseyside, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BKC
Target entity description: BKC is the National Rail station code for Birkenhead Central railway station in Merseyside, England.
  • A. BKC
    BKC is the commonly used abbreviation for Ritsumeikan University's Biwako-Kusatsu Campus in Shiga Prefecture, Japan.
  • B. RBKC
    RBKC is the commonly used abbreviation for the Royal Borough of Kensington and Chelsea, a central London local authority area known for its affluent neighborhoods and cultural landmarks.
  • C. Kannai business district
    Kannai business district is a central commercial and administrative area of Yokohama known for its government offices, corporate buildings, and historic urban streetscape.
  • D. BKH
    BKH is the National Rail station code for Blackheath railway station in southeast London, England.
  • E. Kappabashi
    Kappabashi is a famous Tokyo shopping street and district known for its many stores specializing in kitchenware, restaurant supplies, and realistic plastic food models.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04eb4301881908c7157227fdf79b6 completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f43191c81908c5704314a002608 completed May 9, 2026, 4:22 p.m.
NEDg Description generation batch_69ff5ffaefb4819094468ff0008740f8 completed May 9, 2026, 4:25 p.m.
NED2 Entity disambiguation (via description) batch_69ff6062f0ac819081270f270ce2f057 completed May 9, 2026, 4:27 p.m.
Created at: April 10, 2026, 4:14 a.m.