Triple

T4142167
Position Surface form Disambiguated ID Type / Status
Subject Wembley E89294 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Sudbury E299682 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: Sudbury | Statement: [Wembley, hasNeighbourhood, Sudbury]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sudbury
Context triple: [Wembley, hasNeighbourhood, Sudbury]
  • A. Sudbury
    Sudbury is a major city in northern Ontario, Canada, known for its mining industry and numerous surrounding lakes.
  • B. Sudbury chosen
    Sudbury is a historic market town in Suffolk, England, known for its medieval architecture and association with painter Thomas Gainsborough.
  • C. Sudbury, Massachusetts
    Sudbury, Massachusetts is a historic New England town west of Boston known for its colonial heritage, affluent residential character, and preserved rural landscapes.
  • D. Fitchburg
    Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
  • E. Haverhill
    Haverhill is a market town in Suffolk, England, known for its growing population, light industry, and role as a commuter hub for nearby larger cities.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af024cc7e88190b23b39d6f5f2a2e0 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f2e787881908a9721877b0fd4ae completed March 14, 2026, 3:30 p.m.
Created at: March 9, 2026, 3:43 p.m.