Triple

T9862435
Position Surface form Disambiguated ID Type / Status
Subject Bank Underground station E239747 entity
Predicate hasStationCode P1289 FINISHED
Object ZBA
ZBA is the National Rail station code assigned to Bank Underground station in London.
 E826160 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: ZBA | Statement: [Bank Underground station, hasStationCode, ZBA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZBA
Context triple: [Bank Underground station, hasStationCode, ZBA]
  • A. BZA
    BZA is the station code for Vijayawada Junction, one of the busiest and most important railway hubs in the Indian Railways network.
  • B. ZBAD
    ZBAD is the ICAO airport code for Beijing Daxing International Airport, the major international aviation hub serving Beijing, China.
  • C. ZA
    ZA is the ISO 3166-1 alpha-2 country code for South Africa.
  • D. ZBH
    ZBH is the stock ticker symbol for Zimmer Biomet Holdings, Inc., a major medical device company specializing in musculoskeletal healthcare products.
  • E. ZAZ
    ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
  • 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: ZBA
Triple: [Bank Underground station, hasStationCode, ZBA]
Generated description
ZBA is the National Rail station code assigned to Bank Underground station in London.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZBA
Target entity description: ZBA is the National Rail station code assigned to Bank Underground station in London.
  • A. BZA
    BZA is the station code for Vijayawada Junction, one of the busiest and most important railway hubs in the Indian Railways network.
  • B. ZBAD
    ZBAD is the ICAO airport code for Beijing Daxing International Airport, the major international aviation hub serving Beijing, China.
  • C. ZA
    ZA is the ISO 3166-1 alpha-2 country code for South Africa.
  • D. ZBH
    ZBH is the stock ticker symbol for Zimmer Biomet Holdings, Inc., a major medical device company specializing in musculoskeletal healthcare products.
  • E. ZAZ
    ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3b7b81c81909a84f6ced829f394 completed April 2, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e447d3dc819090268f7d14ba3be4 completed April 5, 2026, 4:25 a.m.
NEDg Description generation batch_69d1e4bdd10881909d03bac4912e8e0a completed April 5, 2026, 4:27 a.m.
NED2 Entity disambiguation (via description) batch_69d1e5358b148190a6e432aac9d02544 completed April 5, 2026, 4:29 a.m.
Created at: March 30, 2026, 8:35 p.m.