Triple

T26781439
Position Surface form Disambiguated ID Type / Status
Subject Verona, Kentucky E670257 entity
Predicate roadJunctionOf P6234 FINISHED
Object Kentucky Route 491
Kentucky Route 491 is a state highway in Kentucky that serves the Verona area and connects it to surrounding communities and routes.
E1758164 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: Kentucky Route 491 | Statement: [Verona, Kentucky, roadJunctionOf, Kentucky Route 491]
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: Kentucky Route 491
Triple: [Verona, Kentucky, roadJunctionOf, Kentucky Route 491]
Generated description
Kentucky Route 491 is a state highway in Kentucky that serves the Verona area and connects it to surrounding communities and 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_69eeb31c925881909b597f6e40056d28 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f6197ad524819086c1e2de6a3b52a9 completed May 2, 2026, 3:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1247dd91b881909e51a08f92865eba completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a1249b3e9888190b3bae29310007be4 completed May 24, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_6a124a849c3c81908f1b3acdbaed65f8 completed May 24, 2026, 12:47 a.m.
Created at: April 27, 2026, 4:09 a.m.