Triple

T3807954
Position Surface form Disambiguated ID Type / Status
Subject Wilmslow railway station E93054 entity
Predicate stationCode P1289 FINISHED
Object WML
WML is the National Rail station code for Wilmslow railway station in Cheshire, England.
 E391664 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: WML | Statement: [Wilmslow railway station, stationCode, WML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WML
Context triple: [Wilmslow railway station, stationCode, WML]
  • A. WLM
    WLM (Workload Manager) is an IBM z/OS component that dynamically manages and prioritizes system workloads to meet performance goals and service-level objectives.
  • B. WMC
    WMC is the commonly used abbreviation for the World Methodist Council, a worldwide association of Methodist churches and related denominations.
  • C. LWP
    LWP is the abbreviation for the Polish People’s Army, the communist-era armed forces of Poland that existed from the end of World War II until 1989.
  • D. HTM
    HTM is the public transport company that operates trams and buses in and around The Hague in the Netherlands.
  • E. W3
    W3 is a common shorthand for the World Wide Web, the global system of interlinked hypertext documents and resources accessed via the internet.
  • 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: WML
Triple: [Wilmslow railway station, stationCode, WML]
Generated description
WML is the National Rail station code for Wilmslow railway station in Cheshire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WML
Target entity description: WML is the National Rail station code for Wilmslow railway station in Cheshire, England.
  • A. WLM
    WLM (Workload Manager) is an IBM z/OS component that dynamically manages and prioritizes system workloads to meet performance goals and service-level objectives.
  • B. WMC
    WMC is the commonly used abbreviation for the World Methodist Council, a worldwide association of Methodist churches and related denominations.
  • C. LWP
    LWP is the abbreviation for the Polish People’s Army, the communist-era armed forces of Poland that existed from the end of World War II until 1989.
  • D. HTM
    HTM is the public transport company that operates trams and buses in and around The Hague in the Netherlands.
  • E. W3
    W3 is a common shorthand for the World Wide Web, the global system of interlinked hypertext documents and resources accessed via the internet.
  • 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee80b02888190b2d778feef14f576 completed March 9, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb30a61c819096325d7f11d22f89 completed March 14, 2026, 6:07 a.m.
NEDg Description generation batch_69b4fbd93b1481909f89d807ef870aa7 completed March 14, 2026, 6:10 a.m.
NED2 Entity disambiguation (via description) batch_69b4ffc51bc08190aef4548a351b5604 completed March 14, 2026, 6:27 a.m.
Created at: March 9, 2026, 3:16 p.m.