Triple

T809964
Position Surface form Disambiguated ID Type / Status
Subject Virtuous Well E17521 entity
Predicate locatedIn P40 FINISHED
Object Monmouthshire E27493 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: Monmouthshire | Statement: [Virtuous Well, locatedIn, Monmouthshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monmouthshire
Context triple: [Virtuous Well, locatedIn, Monmouthshire]
  • A. Monmouthshire chosen
    Monmouthshire is a historic county and principal area in southeast Wales, known for its rural landscapes, market towns, and rich medieval heritage.
  • B. Montgomeryshire
    Montgomeryshire is a historic county and former parliamentary constituency in mid-Wales, known for its rural landscape and market towns such as Newtown and Welshpool.
  • C. Denbighshire
    Denbighshire is a historic and principal county in north-east Wales, known for its rural landscapes, market towns, and sections of the Clwydian Range and Dee Valley Area of Outstanding Natural Beauty.
  • D. Pembrokeshire
    Pembrokeshire is a coastal county in southwest Wales renowned for its rugged cliffs, sandy beaches, and the Pembrokeshire Coast National Park.
  • E. Powys
    Powys is a large, predominantly rural county in mid-Wales known for its mountainous landscapes, market towns, and extensive agricultural areas.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab26d36c8190800e98890b7ae08e completed March 1, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac427da0348190a8ae16db2a048d0b completed March 7, 2026, 3:21 p.m.
Created at: March 1, 2026, 7:38 p.m.