Triple

T27387864
Position Surface form Disambiguated ID Type / Status
Subject Gates County, North Carolina E691432 entity
Predicate hasSettlement P1068 FINISHED
Object Sunbury, North Carolina
Sunbury, North Carolina is a small unincorporated rural community located in northeastern North Carolina near the Virginia border.
E1809858 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: Sunbury, North Carolina | Statement: [Gates County, North Carolina, hasSettlement, Sunbury, North Carolina]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sunbury, North Carolina
Triple: [Gates County, North Carolina, hasSettlement, Sunbury, North Carolina]
Generated description
Sunbury, North Carolina is a small unincorporated rural community located in northeastern North Carolina near the Virginia border.

Provenance (5 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_69ef520386788190bc92cfcd97ebb67a completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62c8d15d48190825465932c36a6c3 completed May 2, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1606eb2658819082d0580313f153aa completed May 26, 2026, 8:47 p.m.
NEDg Description generation batch_6a160be48fc48190a447fef91a58282c completed May 26, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_6a160c61f0a88190800ca660556b612f completed May 26, 2026, 9:10 p.m.
Created at: April 27, 2026, 12:25 p.m.