Triple

T6130454
Position Surface form Disambiguated ID Type / Status
Subject A57 road E136703 entity
Predicate passesThrough P225 FINISHED
Object Manchester E114 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: Manchester | Statement: [A57 road, passesThrough, Manchester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manchester
Context triple: [A57 road, passesThrough, Manchester]
  • A. Manchester
    Manchester is a suburban town in central Connecticut known for its historic mills, shopping districts, and residential communities within the Greater Hartford area.
  • B. Manchester chosen
    Manchester is a major city in northwest England known for its industrial heritage, vibrant cultural scene, and influential contributions to music, sport, and science.
  • C. Manchester
    Manchester is the most populous city in the U.S. state of New Hampshire and a major economic and cultural center for the region.
  • D. Manchester
    Manchester is a historic neighborhood on Pittsburgh’s North Side known for its 19th-century architecture and designation as a historic district.
  • E. York
    York is a historic walled city in North Yorkshire, England, renowned for its medieval architecture, including York Minster, and its rich Roman and Viking heritage.
  • 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_69c008a0a37c81908e5b4f879158afb3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05c4de9c48190b98f67a6251ec1df completed March 22, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16eb7a0548190ab661b0e68a4ef47 completed March 23, 2026, 4:47 p.m.
Created at: March 22, 2026, 4:15 p.m.