Triple

T13587022
Position Surface form Disambiguated ID Type / Status
Subject Ayton E324592 entity
Predicate locatedOn P40 FINISHED
Object Eye Water E324599 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: Eye Water | Statement: [Ayton, locatedOn, Eye Water]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eye Water
Context triple: [Ayton, locatedOn, Eye Water]
  • A. Eye Water chosen
    Eye Water is a river in the Scottish Borders region of Berwickshire, known for flowing through rural landscapes before reaching the North Sea.
  • B. Eye
    Eye is a small historic market town in Suffolk, England, known for its medieval architecture and rural surroundings.
  • C. Eyes
    "Eyes" is a multimedia artwork by American video artist Tony Oursler, known for its haunting projected imagery that explores themes of perception and psychological unease.
  • D. River Eye
    The River Eye is a small river in Gloucestershire, England, known for flowing through the Cotswold countryside and picturesque villages before joining the River Windrush.
  • E. River Eye
    The River Eye is a small river in eastern England that flows through rural Leicestershire before joining the River Witham.
  • 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb054c6008190839384ce26e8f71a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc148d08190821614a866d1a7f0 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:49 p.m.