Triple

T2271599
Position Surface form Disambiguated ID Type / Status
Subject London Waterloo railway station E50670 entity
Predicate railCode P18202 FINISHED
Object WAT
WAT is the National Rail station code for London Waterloo, one of the busiest and most important railway terminals in the United Kingdom.
 E250114 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: WAT | Statement: [London Waterloo railway station, railCode, WAT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WAT
Context triple: [London Waterloo railway station, railCode, WAT]
  • A. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • B. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • C. WAS
    WAS is the standard three-letter abbreviation used for the NBA team Washington Wizards.
  • D. Waic
    Waic is a subgroup of related Austroasiatic languages spoken primarily by the Wa people in parts of China and Myanmar.
  • E. Na Wa Ta
    Na Wa Ta is the Burmese-language acronym for Myanmar’s former military junta, the State Law and Order Restoration Council, which ruled the country after the 1988 coup.
  • 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: WAT
Triple: [London Waterloo railway station, railCode, WAT]
Generated description
WAT is the National Rail station code for London Waterloo, one of the busiest and most important railway terminals in the United Kingdom.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WAT
Target entity description: WAT is the National Rail station code for London Waterloo, one of the busiest and most important railway terminals in the United Kingdom.
  • A. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • B. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • C. WAS
    WAS is the standard three-letter abbreviation used for the NBA team Washington Wizards.
  • D. Waic
    Waic is a subgroup of related Austroasiatic languages spoken primarily by the Wa people in parts of China and Myanmar.
  • E. Na Wa Ta
    Na Wa Ta is the Burmese-language acronym for Myanmar’s former military junta, the State Law and Order Restoration Council, which ruled the country after the 1988 coup.
  • 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_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1c0de488190876b644cdaa41637 completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71db927c8190a76cfb873039b04b completed March 9, 2026, 7:08 a.m.
NEDg Description generation batch_69ae7486bf808190a732e5eb7744b087 completed March 9, 2026, 7:19 a.m.
NED2 Entity disambiguation (via description) batch_69ae74eb89448190895fab4a493c6d08 completed March 9, 2026, 7:21 a.m.
Created at: March 4, 2026, 7:48 p.m.