Triple

T2476184
Position Surface form Disambiguated ID Type / Status
Subject Euston Underground station E55093 entity
Predicate hasStationCode P1289 FINISHED
Object EUS E51945 NE FINISHED

How this triple was built (2 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: EUS | Statement: [Euston Underground station, hasStationCode, EUS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EUS
Context triple: [Euston Underground station, hasStationCode, EUS]
  • A. EUS chosen
    EUS is the three-letter National Rail station code for London Euston, a major central London railway terminus.
  • B. ESU
    ESU is a specialized police emergency response unit that handles high-risk situations such as tactical operations, rescues, and hazardous incidents.
  • C. USZ
    USZ is a major public teaching hospital in Zurich, Switzerland, affiliated with the University of Zurich and known for its advanced medical care and research.
  • D. EUG
    EUG is the IATA airport code for Mahlon Sweet Field, the primary commercial airport serving Eugene and the surrounding region in western Oregon, United States.
  • E. DUS
    DUS is the three-letter IATA code for Düsseldorf Airport, a major international airport in western Germany.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ab49e279e88190ab10d7248aea9d11 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd14c8c388190bbdc486ffed6899e completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17ab837881909bf8704acf9598e4 completed March 9, 2026, 6:55 p.m.
Created at: March 6, 2026, 9:45 p.m.