Triple

T2986062
Position Surface form Disambiguated ID Type / Status
Subject London commuter belt E80626 entity
Predicate hasTransportHub P2413 FINISHED
Object Reading E22663 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: Reading | Statement: [London commuter belt, hasTransportHub, Reading]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reading
Context triple: [London commuter belt, hasTransportHub, Reading]
  • A. Reading chosen
    Reading is a major town in Berkshire, England, known as a key commercial and transport hub in the Thames Valley.
  • B. Reading
    Reading is a historic city in southeastern Pennsylvania known for its industrial heritage, transportation links, and role as a regional cultural and economic center.
  • C. Reading
    "Reading" is an Impressionist painting by Berthe Morisot that depicts a quiet, intimate moment of a woman absorbed in a book.
  • D. Read
    Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
  • E. The Right to Read
    "The Right to Read" is a short story by Richard Stallman that warns about the dangers of restrictive digital rights management and the loss of freedoms in a future where sharing digital works is criminalized.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99c76dfc8190b08bd6110ffabf25 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108fb46b08190bcbd00e69cf06047 completed March 11, 2026, 6:17 a.m.
Created at: March 8, 2026, 2:59 p.m.