Triple

T10121413
Position Surface form Disambiguated ID Type / Status
Subject University of Huddersfield E223298 entity
Predicate locatedIn P40 FINISHED
Object Huddersfield E42265 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: Huddersfield | Statement: [University of Huddersfield, locatedIn, Huddersfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huddersfield
Context triple: [University of Huddersfield, locatedIn, Huddersfield]
  • A. Huddersfield chosen
    Huddersfield is a large market town in West Yorkshire, England, known for its Victorian architecture, university, and role in the Industrial Revolution.
  • B. Todmorden
    Todmorden is a market town in West Yorkshire, England, known for its industrial heritage, surrounding Pennine countryside, and community-led urban agriculture initiatives.
  • C. Bradford
    Bradford is a town in Ontario, Canada, serving as the main urban centre of the municipality of Bradford West Gwillimbury.
  • D. Bradford
    Bradford is a masculine given name of Old English origin, traditionally meaning "broad ford" and used both as a first name and surname.
  • E. Bradford
    Bradford is a major city in West Yorkshire, Northern England, known for its industrial heritage, diverse population, and role in the wool and textile industries.
  • 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_69ca8422047c81909d66b717b8b18cf3 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd266b18c8190b35fe637c912e756 completed April 2, 2026, 2:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc493db88190b3b09a77b82b3cc9 completed April 5, 2026, 8:55 p.m.
Created at: March 30, 2026, 9:04 p.m.