Triple

T4295512
Position Surface form Disambiguated ID Type / Status
Subject Westminster Underground Station E99700 entity
Predicate stationCode P1289 FINISHED
Object WES
WES is the three-letter station code used to identify Westminster Underground Station on the London Underground network.
 E428436 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: WES | Statement: [Westminster Underground Station, stationCode, WES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WES
Context triple: [Westminster Underground Station, stationCode, WES]
  • A. WES
    WES is a commuter rail service in the Portland, Oregon metropolitan area that connects Beaverton and Wilsonville.
  • B. WES
    WES is the standard abbreviation for the Westchester Knicks, the NBA G League affiliate of the New York Knicks.
  • C. WES
    WES is the historic Chapman code used in genealogical records to represent the former English county of Westmorland.
  • D. WES
    WES is the vehicle registration code used on license plates for vehicles registered in the Wesel district of Germany.
  • E. WST
    WST is the commonly used abbreviation for the World Snooker Tour, the professional circuit for elite snooker players worldwide.
  • 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: WES
Triple: [Westminster Underground Station, stationCode, WES]
Generated description
WES is the three-letter station code used to identify Westminster Underground Station on the London Underground network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WES
Target entity description: WES is the three-letter station code used to identify Westminster Underground Station on the London Underground network.
  • A. WES
    WES is a commuter rail service in the Portland, Oregon metropolitan area that connects Beaverton and Wilsonville.
  • B. WES
    WES is the standard abbreviation for the Westchester Knicks, the NBA G League affiliate of the New York Knicks.
  • C. WES
    WES is the historic Chapman code used in genealogical records to represent the former English county of Westmorland.
  • D. WES
    WES is the vehicle registration code used on license plates for vehicles registered in the Wesel district of Germany.
  • E. WST
    WST is the commonly used abbreviation for the World Snooker Tour, the professional circuit for elite snooker players worldwide.
  • 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_69b3455175088190aa79c6e03b86647e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35085b864819086cf726285384566 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c740c4a081909a63fb957f2926ae completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c7d04508819087b14c5c86f1e015 completed March 14, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_69b5c84ccea08190a8e7e8fa93934ea2 completed March 14, 2026, 8:42 p.m.
Created at: March 12, 2026, 11:08 p.m.