Triple

T15545605
Position Surface form Disambiguated ID Type / Status
Subject Waterloo railway station E370600 entity
Predicate hasStationCode P1289 FINISHED
Object WLO E563495 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: WLO | Statement: [Waterloo railway station, hasStationCode, WLO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WLO
Context triple: [Waterloo railway station, hasStationCode, WLO]
  • A. WLO chosen
    WLO is the National Rail station code used to identify London Waterloo Underground station in the UK rail network.
  • B. WNLO
    WNLO is a major Chinese research institute specializing in optoelectronics and photonics, based in Wuhan.
  • C. WLV
    WLV is the National Rail station code for Wallasey Village railway station on the Wirral Line in Merseyside, England.
  • D. WOB
    WOB is the vehicle registration code used on license plates for cars registered in Wolfsburg, Germany.
  • E. WL
    WL is the station code for Lutherstadt Wittenberg railway station in 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0443410408190a249889edcd9c599 completed April 16, 2026, 2:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff455a38188190a593c70be09d6103 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 4:07 a.m.