Triple

T872877
Position Surface form Disambiguated ID Type / Status
Subject Barchester Towers E18851 entity
Predicate hasFictionalUniverse P3758 FINISHED
Object Barsetshire E98683 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: Barsetshire | Statement: [Barchester Towers, hasFictionalUniverse, Barsetshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barsetshire
Context triple: [Barchester Towers, hasFictionalUniverse, Barsetshire]
  • A. Barsetshire chosen
    Barsetshire is a fictional English county created by Anthony Trollope as the backdrop for his series of Victorian social and clerical novels.
  • B. Herefordshire
    Herefordshire is a predominantly rural county in the West Midlands of England, known for its agriculture, rolling countryside, and the cathedral city of Hereford.
  • C. Banbury
    Banbury is a historic market town in Oxfordshire, England, known for its medieval cross, canal-side setting, and association with the traditional Banbury cake.
  • D. Somerset
    Somerset is a historic county in South West England known for its rural landscapes, coastal areas, and cities such as Bath and Wells.
  • E. Ilchester
    Ilchester is a historic village and former Roman town in Somerset, England, known for its strategic location and long-standing military and transport connections.
  • 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_69a4938db1f081909bcd1ad2713b6096 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2b8063081909566c404ca63a29e completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b84fb2d0819084c256023bc23dc5 completed March 4, 2026, 4:42 a.m.
Created at: March 1, 2026, 7:39 p.m.