Triple

T33483374
Position Surface form Disambiguated ID Type / Status
Subject Huron, South Dakota E857540 entity
Predicate majorHighway P385 FINISHED
Object South Dakota Highway 37
South Dakota Highway 37 is a state highway running north–south through eastern South Dakota, serving communities such as Huron and connecting regional agricultural and commercial areas.
 E815075 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: South Dakota Highway 37 | Statement: [Huron, South Dakota, majorHighway, South Dakota Highway 37]
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: South Dakota Highway 37
Triple: [Huron, South Dakota, majorHighway, South Dakota Highway 37]
Generated description
South Dakota Highway 37 is a state highway running north–south through eastern South Dakota, serving communities such as Huron and connecting regional agricultural and commercial areas.

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_6a36ae2eb9fc819094a80420649ca646 completed June 20, 2026, 3:13 p.m.
NEDg Description generation batch_6a36aef5e62c81909695813abde97094 completed June 20, 2026, 3:17 p.m.
NED2 Entity disambiguation (via description) batch_6a36afe7a9208190952f11924f15856b completed June 20, 2026, 3:21 p.m.
Created at: May 1, 2026, 1:38 a.m.