Triple

T13068654
Position Surface form Disambiguated ID Type / Status
Subject Bamberg, South Carolina E329395 entity
Predicate county P75 FINISHED
Object Bamberg County E713355 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: Bamberg County | Statement: [Bamberg, South Carolina, county, Bamberg County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bamberg County
Context triple: [Bamberg, South Carolina, county, Bamberg County]
  • A. Bamberg County chosen
    Bamberg County is a rural county in South Carolina known for its agricultural landscape and small-town communities in the state’s southern region.
  • B. Randolph County
    Randolph County is a rural county in eastern Alabama known for its small towns, agricultural landscape, and proximity to the Georgia state line.
  • C. Baca County
    Baca County is a sparsely populated, agriculture-focused county located in the southeastern corner of the U.S. state of Colorado.
  • D. Berat County
    Berat County is an administrative region in south-central Albania known for its historic city of Berat, a UNESCO World Heritage site famed for its Ottoman-era architecture and hillside houses.
  • E. Suide County
    Suide County is an administrative county in northern Shaanxi Province, China, known for its historical significance and location along the middle reaches of the Yellow River.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980ec8ba48190baf52c7823482680 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b056ae388190803458d8fd0331e9 completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 9 p.m.