Triple

T33483432
Position Surface form Disambiguated ID Type / Status
Subject Stutsman County, North Dakota E857541 entity
Predicate borders P224 FINISHED
Object Logan County, North Dakota
Logan County, North Dakota is a sparsely populated rural county in south-central North Dakota known for its agricultural landscape and small communities.
E2138757 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: Logan County, North Dakota | Statement: [Stutsman County, North Dakota, borders, Logan County, North Dakota]
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: Logan County, North Dakota
Triple: [Stutsman County, North Dakota, borders, Logan County, North Dakota]
Generated description
Logan County, North Dakota is a sparsely populated rural county in south-central North Dakota known for its agricultural landscape and small communities.

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_69f3497547608190a1a0f2365fb713ee completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e530e490819095ad1629a71ecd5a completed May 3, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a382c94f0a081908331e56e55c0a300 completed June 21, 2026, 6:25 p.m.
NEDg Description generation batch_6a382d71fa54819095ef74046c139e7a completed June 21, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_6a382e1f37188190ac188d12cc6dce07 completed June 21, 2026, 6:31 p.m.
Created at: May 1, 2026, 1:38 a.m.