Triple

T26609209
Position Surface form Disambiguated ID Type / Status
Subject Jackson County, Georgia E667863 entity
Predicate hasHighway P385 FINISHED
Object State Route 334
State Route 334 is a state highway in Georgia that serves local traffic within Jackson County, connecting rural areas to nearby towns and major routes.
 E2292920 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: State Route 334 | Statement: [Jackson County, Georgia, hasHighway, State Route 334]
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: State Route 334
Triple: [Jackson County, Georgia, hasHighway, State Route 334]
Generated description
State Route 334 is a state highway in Georgia that serves local traffic within Jackson County, connecting rural areas to nearby towns and major 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_69ee9cfd20348190bb1255d2603efb7a completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f61576b3f48190bc87dcdf685b4532 completed May 2, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a438943e08190bf0ae7a602ec3ff5 completed Aug. 10, 2026, 9:32 p.m.
NEDg Description generation batch_6a7a445bc9e881909f6d446aee6b5edf completed Aug. 10, 2026, 9:36 p.m.
NED2 Entity disambiguation (via description) batch_6a7a45071a8481908bd8cb55371c3d2c completed Aug. 10, 2026, 9:39 p.m.
Created at: April 27, 2026, 2:16 a.m.