Triple

T6347176
Position Surface form Disambiguated ID Type / Status
Subject Cumbernauld railway station E142773 entity
Predicate hasStationCode P1289 FINISHED
Object CUD
CUD is the National Rail station code assigned to Cumbernauld railway station in Scotland.
 E587111 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: CUD | Statement: [Cumbernauld railway station, hasStationCode, CUD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CUD
Context triple: [Cumbernauld railway station, hasStationCode, CUD]
  • A. CUN
    CUN is the IATA airport code for Cancún International Airport, a major gateway for international tourism to Mexico’s Caribbean coast.
  • B. CUZ
    CUZ is the IATA airport code for Alejandro Velasco Astete International Airport serving Cusco, Peru.
  • C. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • D. CU
    CU is the common abbreviation for Chulalongkorn University, a leading public research university in Bangkok, Thailand.
  • E. CU
    CU is the common abbreviation for the Christian Union, a Christian student organization found at many universities.
  • 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: CUD
Triple: [Cumbernauld railway station, hasStationCode, CUD]
Generated description
CUD is the National Rail station code assigned to Cumbernauld railway station in Scotland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CUD
Target entity description: CUD is the National Rail station code assigned to Cumbernauld railway station in Scotland.
  • A. CUN
    CUN is the IATA airport code for Cancún International Airport, a major gateway for international tourism to Mexico’s Caribbean coast.
  • B. CUZ
    CUZ is the IATA airport code for Alejandro Velasco Astete International Airport serving Cusco, Peru.
  • C. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • D. CU
    CU is the common abbreviation for Chulalongkorn University, a leading public research university in Bangkok, Thailand.
  • E. CU
    CU is the common abbreviation for the Christian Union, a Christian student organization found at many universities.
  • 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_69c008d5ab108190b346c465696824a9 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067ba2c64819094fa38bb2aeffa6c completed March 22, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6044b33fc8190a214c6615d072715 completed March 27, 2026, 4:15 a.m.
NEDg Description generation batch_69c6057466ec8190afe96107862bb40a completed March 27, 2026, 4:20 a.m.
NED2 Entity disambiguation (via description) batch_69c6060a113881909b424d0c47c2107e completed March 27, 2026, 4:22 a.m.
Created at: March 22, 2026, 4:31 p.m.