Triple

T13005354
Position Surface form Disambiguated ID Type / Status
Subject Simon Stephens E322270 entity
Predicate notableWork P4 FINISHED
Object Wastwater E120950 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: Wastwater | Statement: [Simon Stephens, notableWork, Wastwater]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wastwater
Context triple: [Simon Stephens, notableWork, Wastwater]
  • A. Wast Water chosen
    Wast Water is a deep, glacial lake in England’s Lake District, renowned for its dramatic surrounding peaks and remote, rugged scenery.
  • B. Achterwasser
    Achterwasser is a coastal lagoon on the German island of Usedom, connected to the Baltic Sea and known for its shallow waters and scenic natural surroundings.
  • C. Lightwater
    Lightwater is a village and civil parish in the English county of Surrey, known for its residential character and proximity to heathland and countryside.
  • D. River Suck
    River Suck is a major river in western Ireland that flows through counties such as Roscommon and Galway before joining the River Shannon.
  • E. Wasserbillig
    Wasserbillig is a town in eastern Luxembourg on the border with Germany, known as a key cross-border transport and railway junction.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9b27ec8190815c40a05b9ba7d0 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c109e59481909fc46b152034c6a9 completed May 3, 2026, 3:29 a.m.
Created at: April 9, 2026, 8:48 p.m.