Triple

T12314674
Position Surface form Disambiguated ID Type / Status
Subject TfL Rail E293569 entity
Predicate terminus P388 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: [TfL Rail, terminus, Reading]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reading
Context triple: [TfL Rail, terminus, Reading]
  • A. Reading
    "Reading" is an Impressionist painting by Berthe Morisot that depicts a quiet, intimate moment of a woman absorbed in a book.
  • B. Reading chosen
    Reading is a major town in Berkshire, England, known as a key commercial and transport hub in the Thames Valley.
  • C. 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.
  • D. Read
    Read is a village in Lancashire, England, situated near the River Calder and known for its residential community and local amenities.
  • E. Read
    Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f05186481909c024a933b4f6c60 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e86d45881909a9a3c09df0b78f1 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:53 p.m.