Triple

T12051693
Position Surface form Disambiguated ID Type / Status
Subject Wokingham railway station E286930 entity
Predicate hasStationCode P1289 FINISHED
Object WKM
WKM is the National Rail station code for Wokingham railway station in Berkshire, England.
 E960869 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: WKM | Statement: [Wokingham railway station, hasStationCode, WKM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WKM
Context triple: [Wokingham railway station, hasStationCode, WKM]
  • A. WKM
    WKM is the abbreviated name for the Warszawska Karta Miejska, Warsaw’s electronic public transport card used for storing and validating tickets.
  • B. KMW
    KMW is a German defense manufacturer best known for producing armored vehicles such as the Leopard 2 main battle tank.
  • C. WK
    WK is the IATA airline designator assigned to Edelweiss Air, a Swiss leisure airline based in Zurich.
  • D. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • E. KMF
    KMF is the ISO 4217 currency code for the Comorian franc, the official monetary unit of the Comoros.
  • 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: WKM
Triple: [Wokingham railway station, hasStationCode, WKM]
Generated description
WKM is the National Rail station code for Wokingham railway station in Berkshire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WKM
Target entity description: WKM is the National Rail station code for Wokingham railway station in Berkshire, England.
  • A. WKM
    WKM is the abbreviated name for the Warszawska Karta Miejska, Warsaw’s electronic public transport card used for storing and validating tickets.
  • B. KMW
    KMW is a German defense manufacturer best known for producing armored vehicles such as the Leopard 2 main battle tank.
  • C. WK
    WK is the IATA airline designator assigned to Edelweiss Air, a Swiss leisure airline based in Zurich.
  • D. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • E. KMF
    KMF is the ISO 4217 currency code for the Comorian franc, the official monetary unit of the Comoros.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90423b22081908fba82fbc6b40eb5 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49ddde6548190adae2a889ec5c72b completed May 1, 2026, 12:34 p.m.
NEDg Description generation batch_69f53d95d4fc8190b5f4e460646bec2a completed May 1, 2026, 11:56 p.m.
NED2 Entity disambiguation (via description) batch_69f56505c0b481909f9caaf338f73033 completed May 2, 2026, 2:44 a.m.
Created at: April 8, 2026, 9:47 p.m.