Triple

T23381140
Position Surface form Disambiguated ID Type / Status
Subject Southwestern Nebraska E593747 entity
Predicate includesCounty P5971 FINISHED
Object Dundy County, Nebraska
Dundy County, Nebraska is a sparsely populated agricultural county in the far southwestern corner of Nebraska, bordering Colorado and Kansas.
E1707292 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: Dundy County, Nebraska | Statement: [Southwestern Nebraska, includesCounty, Dundy County, Nebraska]
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: Dundy County, Nebraska
Triple: [Southwestern Nebraska, includesCounty, Dundy County, Nebraska]
Generated description
Dundy County, Nebraska is a sparsely populated agricultural county in the far southwestern corner of Nebraska, bordering Colorado and Kansas.

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_69e25d268a50819095f2fd479da8ef3f completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a3b7eff48190be126df2211b4c85 completed April 29, 2026, 6:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a111ad5a13c81908f4cf10fa287eaa6 completed May 23, 2026, 3:11 a.m.
NEDg Description generation batch_6a111bd7e1188190b3275dc1efe4bfb3 completed May 23, 2026, 3:15 a.m.
NED2 Entity disambiguation (via description) batch_6a111cbb1ed88190a4980f8fc8a0a19f completed May 23, 2026, 3:19 a.m.
Created at: April 17, 2026, 5:34 p.m.