Triple

T5612522
Position Surface form Disambiguated ID Type / Status
Subject Whinhill railway station E147390 entity
Predicate stationCode P1289 FINISHED
Object WNL
WNL is the National Rail station code for Whinhill railway station in Inverclyde, Scotland.
 E533938 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: WNL | Statement: [Whinhill railway station, stationCode, WNL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WNL
Context triple: [Whinhill railway station, stationCode, WNL]
  • A. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • B. NWL
    NWL is the stock ticker symbol for Newell Brands Inc., a consumer goods company known for products under brands like Rubbermaid, Sharpie, and Coleman.
  • C. WNLO
    WNLO is a major Chinese research institute specializing in optoelectronics and photonics, based in Wuhan.
  • D. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • E. WUN
    WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
  • 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: WNL
Triple: [Whinhill railway station, stationCode, WNL]
Generated description
WNL is the National Rail station code for Whinhill railway station in Inverclyde, Scotland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WNL
Target entity description: WNL is the National Rail station code for Whinhill railway station in Inverclyde, Scotland.
  • A. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • B. NWL
    NWL is the stock ticker symbol for Newell Brands Inc., a consumer goods company known for products under brands like Rubbermaid, Sharpie, and Coleman.
  • C. WNLO
    WNLO is a major Chinese research institute specializing in optoelectronics and photonics, based in Wuhan.
  • D. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • E. WUN
    WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
  • 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_69c00905d4588190bd967842bbcf2219 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0212143708190b5234407334ab216 completed March 22, 2026, 5:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0287b14708190bc246e982896ad27 completed March 22, 2026, 5:35 p.m.
NEDg Description generation batch_69c03f8b6e948190870b98d6d69193fe completed March 22, 2026, 7:14 p.m.
NED2 Entity disambiguation (via description) batch_69c0404f0a3081908850794f9a5cea40 completed March 22, 2026, 7:17 p.m.
Created at: March 22, 2026, 3:39 p.m.