Triple

T7990042
Position Surface form Disambiguated ID Type / Status
Subject Leicestershire E185975 entity
Predicate hasRiver P165 FINISHED
Object River Wreake E457930 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: River Wreake | Statement: [Leicestershire, hasRiver, River Wreake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: River Wreake
Context triple: [Leicestershire, hasRiver, River Wreake]
  • A. River Wreake chosen
    River Wreake is a small river in Leicestershire, England, known for flowing through the Wreake Valley and joining the River Soar near Syston.
  • B. Ravage
    Ravage is a Decepticon spy and attack beast in the Transformers franchise, typically depicted as a stealthy, feline-like robot that specializes in infiltration and reconnaissance.
  • C. Marrowbone
    Marrowbone is a 2017 psychological horror-thriller film about a group of siblings hiding dark family secrets in a decaying rural mansion.
  • D. Sea of Thirst
    Sea of Thirst is a vast, dust-filled lunar basin in Arthur C. Clarke’s science fiction novel "A Fall of Moondust," serving as the perilous setting for the story’s central disaster.
  • E. The Killing Ground
    The Killing Ground is a thriller novel by Jack Higgins featuring his recurring character Sean Dillon in a high-stakes tale of terrorism, kidnapping, and covert operations.
  • 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_69ca829c6c308190ab05b43d234c52b2 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c4f98808190879113ad4af9bb4d completed March 31, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0f5c22881908044a178d670684c completed March 31, 2026, 2:57 p.m.
Created at: March 30, 2026, 5:16 p.m.