Triple

T16416250
Position Surface form Disambiguated ID Type / Status
Subject Ralph Brownrigg E398691 entity
Predicate workLocation P7 FINISHED
Object Exeter E122858 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: Exeter | Statement: [Ralph Brownrigg, workLocation, Exeter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Exeter
Context triple: [Ralph Brownrigg, workLocation, Exeter]
  • A. Exeter chosen
    Exeter is a historic cathedral city in Devon, England, known for its medieval architecture and role as a regional administrative and cultural center.
  • B. Exeter
    Exeter is a historic town in Rockingham County, New Hampshire, known for its colonial heritage and as the home of the prestigious Phillips Exeter Academy.
  • C. Exeter
    Exeter is a small borough in Luzerne County, Pennsylvania, situated in the Wyoming Valley near the Susquehanna River.
  • D. Exeter
    Exeter is a small town located in Otsego County in central New York State, known for its rural character and agricultural landscape.
  • E. Exeter
    Exeter is a small village in the Southern Highlands of New South Wales, Australia, known for its rural charm, cool climate, and English-style gardens and architecture.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32877ff248190886717d3329421a7 completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00581245108190842cfd68ec640236 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:09 a.m.