Triple

T6719757
Position Surface form Disambiguated ID Type / Status
Subject Cheltenham Spa railway station E153364 entity
Predicate railwayStationCode P1289 FINISHED
Object CNM
CNM is the National Rail station code for Cheltenham Spa railway station in Gloucestershire, England.
 E613983 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: CNM | Statement: [Cheltenham Spa railway station, railwayStationCode, CNM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CNM
Context triple: [Cheltenham Spa railway station, railwayStationCode, CNM]
  • A. NMMNHS
    NMMNHS is a museum in Albuquerque dedicated to preserving and interpreting New Mexico’s natural history and scientific heritage through exhibits, research, and educational programs.
  • B. NMH
    NMH is the commonly used abbreviation for the Norwegian Academy of Music, a leading institution for higher music education and research in Norway.
  • C. NMC
    NMC is the abbreviated name commonly used for the Nagpur Municipal Corporation, the civic governing body of Nagpur city in Maharashtra, India.
  • D. CMN
    CMN is Chile’s National Monuments Council, the governmental body responsible for protecting and managing the country’s cultural and historical heritage sites.
  • E. CMN
    CMN is the IATA airport code for Mohammed V International Airport, the main international gateway serving Casablanca and one of the busiest airports in Morocco.
  • 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: CNM
Triple: [Cheltenham Spa railway station, railwayStationCode, CNM]
Generated description
CNM is the National Rail station code for Cheltenham Spa railway station in Gloucestershire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CNM
Target entity description: CNM is the National Rail station code for Cheltenham Spa railway station in Gloucestershire, England.
  • A. NMMNHS
    NMMNHS is a museum in Albuquerque dedicated to preserving and interpreting New Mexico’s natural history and scientific heritage through exhibits, research, and educational programs.
  • B. NMH
    NMH is the commonly used abbreviation for the Norwegian Academy of Music, a leading institution for higher music education and research in Norway.
  • C. NMC
    NMC is the abbreviated name commonly used for the Nagpur Municipal Corporation, the civic governing body of Nagpur city in Maharashtra, India.
  • D. CMN
    CMN is Chile’s National Monuments Council, the governmental body responsible for protecting and managing the country’s cultural and historical heritage sites.
  • E. CMN
    CMN is the IATA airport code for Mohammed V International Airport, the main international gateway serving Casablanca and one of the busiest airports in Morocco.
  • 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d137084881908e04ee6b2bd45585 completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7009f1e208190891c4542a6c613ac completed March 27, 2026, 10:11 p.m.
NEDg Description generation batch_69c7048843e081908b70942a91a390fe completed March 27, 2026, 10:28 p.m.
NED2 Entity disambiguation (via description) batch_69c705240f54819094e8715ffd66b352 completed March 27, 2026, 10:31 p.m.
Created at: March 27, 2026, 2:07 p.m.