Triple

T35910273
Position Surface form Disambiguated ID Type / Status
Subject Nebraska Highway 4 E1038587 entity
Predicate connectsTo P845 FINISHED
Object Nebraska Highway 105
Nebraska Highway 105 is a state highway in southeastern Nebraska that runs north–south through rural farmland, connecting small communities and intersecting several other state routes.
 E2169544 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: Nebraska Highway 105 | Statement: [Nebraska Highway 4, connectsTo, Nebraska Highway 105]
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: Nebraska Highway 105
Triple: [Nebraska Highway 4, connectsTo, Nebraska Highway 105]
Generated description
Nebraska Highway 105 is a state highway in southeastern Nebraska that runs north–south through rural farmland, connecting small communities and intersecting several other state 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_69f76e2259608190bf6788a132e0d139 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa73415c81908e54c77484bbac7a completed May 3, 2026, 8:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38dded296c8190825beac69fde1445 completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38f300774c8190a5821266b6940b6f completed June 22, 2026, 8:32 a.m.
NED2 Entity disambiguation (via description) batch_6a38f5f181988190a4fa93c23eb6f175 completed June 22, 2026, 8:44 a.m.
Created at: May 3, 2026, 4:07 p.m.