Triple

T20000839
Position Surface form Disambiguated ID Type / Status
Subject Adlington railway station E494320 entity
Predicate typicalDestinations P6093 FINISHED
Object Manchester NE NERFINISHED

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: [Adlington railway station, typicalDestinations, Manchester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manchester
Context triple: [Adlington railway station, typicalDestinations, Manchester]
  • A. 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.
  • B. 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.
  • C. Manchester
    Manchester is a historic neighborhood on Pittsburgh’s North Side known for its 19th-century architecture and designation as a historic district.
  • D. Manchester
    Manchester is a suburban town in central Connecticut known for its historic mills, shopping districts, and residential communities within the Greater Hartford area.
  • E. Manchester
    Manchester is a common English surname, notably borne by American singer and songwriter Melissa Manchester.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a15f308190a99ac3205f948acb completed April 20, 2026, 5:25 p.m.
Created at: April 11, 2026, 3:32 p.m.