Triple

T13691022
Position Surface form Disambiguated ID Type / Status
Subject Herringswell E328259 entity
Predicate locatedNear P294 FINISHED
Object Tuddenham E299727 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: Tuddenham | Statement: [Herringswell, locatedNear, Tuddenham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tuddenham
Context triple: [Herringswell, locatedNear, Tuddenham]
  • A. Tuddenham chosen
    Tuddenham is a village and civil parish located in the county of Suffolk in eastern England.
  • B. Tillingham
    Tillingham is a small rural village and civil parish in the Maldon District of Essex, England, known for its historic church and traditional English countryside setting.
  • C. Tesseney
    Tesseney is a town in western Eritrea near the Sudanese border, serving as a local commercial and agricultural center in the Gash-Barka region.
  • D. Dunton
    Dunton is a major automotive engineering and design center in the United Kingdom, best known as Ford of Europe’s primary research and development facility.
  • E. Manton
    Manton is a small unincorporated community located in Nelson County, Kentucky, known for its rural setting within the state's central region.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc8746458819095ec1ba3c01ef31b completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7944b93d88190806d6b5735f7e794 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.