Triple

T716355
Position Surface form Disambiguated ID Type / Status
Subject Haverhill Line E14322 entity
Predicate servesMunicipality P3936 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: [Haverhill Line, servesMunicipality, Reading]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reading
Context triple: [Haverhill Line, servesMunicipality, 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. Read
    Read is a surname shared by various notable individuals across fields such as politics, arts, and academia.
  • C. 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.
  • D. Woman Reading
    Woman Reading is a painting by French artist Henri Matisse that exemplifies his use of bold color and simplified forms to depict an intimate, contemplative interior scene.
  • E. Literature
    Literature is the body of written works, especially those considered to have artistic or intellectual value, encompassing genres such as poetry, fiction, drama, and essays across cultures and historical periods.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a57649dc8190bfdee2f9c0c90415 completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dcb5578c8190b5380f1994fdb4d2 completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:37 p.m.