Triple

T14856888
Position Surface form Disambiguated ID Type / Status
Subject CrossCountry Route E349380 entity
Predicate connectsCity P4245 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: [CrossCountry Route, connectsCity, Reading]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reading
Context triple: [CrossCountry Route, connectsCity, Reading]
  • A. 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.
  • 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 an Impressionist painting by Berthe Morisot that depicts a quiet, intimate moment of a woman absorbed in a book.
  • D. Lectura
    Lectura is an earlier version of John Duns Scotus’s theological commentary on Peter Lombard’s Sentences, preceding and later revised into the more polished Ordinatio.
  • E. Read
    Read is a village in Lancashire, England, situated near the River Calder and known for its residential community and local amenities.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded44458ec8190be295a95f5daab14 completed April 14, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe65087708819084f51a043e5361e9 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:54 a.m.