Triple

T4037467
Position Surface form Disambiguated ID Type / Status
Subject Berkshire E83859 entity
Predicate historicalRegion P915 FINISHED
Object Home Counties E35879 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: Home Counties | Statement: [Berkshire, historicalRegion, Home Counties]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Home Counties
Context triple: [Berkshire, historicalRegion, Home Counties]
  • A. Home Counties chosen
    The Home Counties are the traditionally affluent and largely suburban counties surrounding London in southeast England, often associated with commuter towns and a high quality of life.
  • B. Canadian County
    Canadian County is a county in central Oklahoma that forms part of the Oklahoma City metropolitan area.
  • C. Condado
    Condado is an upscale beachfront district in San Juan, Puerto Rico, known for its hotels, casinos, shopping, and vibrant nightlife.
  • D. Somerset County
    Somerset County is a rural, mountainous county in southwestern Pennsylvania known for its outdoor recreation, wind farms, and historic sites such as the Flight 93 National Memorial.
  • E. Somerset County
    Somerset County is a suburban county in central New Jersey known for its residential communities, parks, and commuter access to the New York City metropolitan area.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb3656f08190aa5286d951013646 completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5564436788190aff89ebfeeed6d9b completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:36 p.m.