Triple

T20258767
Position Surface form Disambiguated ID Type / Status
Subject Ticknall E498774 entity
Predicate near P350 FINISHED
Object Ashby-de-la-Zouch 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: Ashby-de-la-Zouch | Statement: [Ticknall, near, Ashby-de-la-Zouch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashby-de-la-Zouch
Context triple: [Ticknall, near, Ashby-de-la-Zouch]
  • A. Ashby-de-la-Zouch chosen
    Ashby-de-la-Zouch is a historic market town in the English Midlands, noted for its medieval castle ruins and Georgian architecture.
  • B. Ashby
    Ashby is a small town in north-central Massachusetts, United States, known for its rural character and proximity to the city of Fitchburg.
  • C. Ashby
    Ashby is a small rural community located within the township of Addington Highlands in eastern Ontario, Canada.
  • D. Ashby
    Ashby is a small rural locality in the Clarence Valley region of New South Wales, Australia, known for its riverside setting and quiet village atmosphere.
  • E. Ashby
    Ashby is a 2015 coming-of-age dramedy film in which Nat Wolff plays a high school student who befriends a retired CIA assassin, portrayed by Mickey Rourke.
  • 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_69da6275fa6c8190952924930adee150 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e674c84e848190a6e8956698b84026 completed April 20, 2026, 6:47 p.m.
Created at: April 11, 2026, 11:41 p.m.