Triple

T20252431
Position Surface form Disambiguated ID Type / Status
Subject Nantwich railway station E498591 entity
Predicate hasStationCode P1289 FINISHED
Object NAN
NAN is the National Rail station code assigned to Nantwich railway station in Cheshire, England.
 E1420467 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: NAN | Statement: [Nantwich railway station, hasStationCode, NAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NAN
Context triple: [Nantwich railway station, hasStationCode, NAN]
  • A. NAN
    NAN is the three-letter IATA airport code for Nadi International Airport in Fiji.
  • B. nan
    nan is the ISO 639-3 language code assigned to the Teochew (Chaoshan) Chinese language variety spoken primarily in eastern Guangdong, China, and among overseas Chinese communities.
  • C. NA
    NA is the commonly used abbreviation for the National Assembly of Pakistan, the lower house of the country's bicameral parliament.
  • D. NA
    The NA is the land warfare branch and largest component of the Nigerian Armed Forces, responsible for ground military operations and national defense.
  • E. NA
    NA is the commonly used abbreviation for the National Assembly of Namibia, the country's lower house of Parliament and primary legislative body.
  • 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: NAN
Triple: [Nantwich railway station, hasStationCode, NAN]
Generated description
NAN is the National Rail station code assigned to Nantwich railway station in Cheshire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NAN
Target entity description: NAN is the National Rail station code assigned to Nantwich railway station in Cheshire, England.
  • A. NAN
    NAN is the three-letter IATA airport code for Nadi International Airport in Fiji.
  • B. nan
    nan is the ISO 639-3 language code assigned to the Teochew (Chaoshan) Chinese language variety spoken primarily in eastern Guangdong, China, and among overseas Chinese communities.
  • C. NA
    NA is the commonly used abbreviation for the National Assembly of Pakistan, the lower house of the country's bicameral parliament.
  • D. NA
    The NA is the land warfare branch and largest component of the Nigerian Armed Forces, responsible for ground military operations and national defense.
  • E. NA
    NA is the commonly used abbreviation for the National Assembly of Namibia, the country's lower house of Parliament and primary legislative body.
  • 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e673a986e08190b1ff2992ed5f8772 completed April 20, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0855282a0c8190b6f246521dfbda51 completed May 16, 2026, 11:29 a.m.
NEDg Description generation batch_6a0855c6bab08190831cc78647de84fc completed May 16, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_6a0856e66c808190b5ef994f1cbc5f3e completed May 16, 2026, 11:37 a.m.
Created at: April 11, 2026, 11:41 p.m.