Triple

T35232082
Position Surface form Disambiguated ID Type / Status
Subject Roberts County, South Dakota E1017264 entity
Predicate hasNotableCommunity P1113 FINISHED
Object Summit, South Dakota
Summit, South Dakota is a small rural town in northeastern South Dakota known for its location along major transportation routes and its close-knit community.
E2151115 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: Summit, South Dakota | Statement: [Roberts County, South Dakota, hasNotableCommunity, Summit, South 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: Summit, South Dakota
Triple: [Roberts County, South Dakota, hasNotableCommunity, Summit, South Dakota]
Generated description
Summit, South Dakota is a small rural town in northeastern South Dakota known for its location along major transportation routes and its close-knit community.

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_69f76de12e4c8190bc46b71a32858356 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78eea7eb4819090fb1d5e5c981246 completed May 3, 2026, 6:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387266b5348190be56ab3b2b3fa9e0 completed June 21, 2026, 11:23 p.m.
NEDg Description generation batch_6a38730bbf348190b9ad5a1ef6a659a8 completed June 21, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_6a3873fd9ccc8190ac41f5aaf772bde6 completed June 21, 2026, 11:30 p.m.
Created at: May 3, 2026, 4:02 p.m.