Triple

T26640029
Position Surface form Disambiguated ID Type / Status
Subject Todd County, South Dakota E668751 entity
Predicate hasMajorHighway P385 FINISHED
Object South Dakota Highway 63
South Dakota Highway 63 is a state highway running north–south through central South Dakota, connecting several rural counties and reservations to larger regional routes.
E1841361 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 63 | Statement: [Todd County, South Dakota, hasMajorHighway, South Dakota Highway 63]
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 63
Triple: [Todd County, South Dakota, hasMajorHighway, South Dakota Highway 63]
Generated description
South Dakota Highway 63 is a state highway running north–south through central South Dakota, connecting several rural counties and reservations to larger regional routes.

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_69ee9d0024b8819090a7c8cf669a3b6c completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f616313e788190b2d72b07960f4466 completed May 2, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec1206408190a365efc5099adc69 completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f04a62088190a7c7981e2baab162 completed June 7, 2026, 4:15 a.m.
NED2 Entity disambiguation (via description) batch_6a24f4b1f6bc8190b2edb78cc273e419 completed June 7, 2026, 4:33 a.m.
Created at: April 27, 2026, 2:28 a.m.