Triple

T36392472
Position Surface form Disambiguated ID Type / Status
Subject Vonore, Tennessee E896364 entity
Predicate transportation P230 FINISHED
Object State Route 72
State Route 72 is a Tennessee state highway that serves as a regional connector through communities such as Vonore, facilitating local and through traffic in eastern Tennessee.
 E2297852 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 72 | Statement: [Vonore, Tennessee, transportation, State Route 72]
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 72
Triple: [Vonore, Tennessee, transportation, State Route 72]
Generated description
State Route 72 is a Tennessee state highway that serves as a regional connector through communities such as Vonore, facilitating local and through traffic in eastern Tennessee.

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_69f76e52e3108190becf70b090ae7bd6 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bcda95e48190a7fb9e56b58233de completed May 3, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a83e3a616a48190973075731965b9ce completed Aug. 18, 2026, 4:46 a.m.
NEDg Description generation batch_6a83e4732e84819086920f916a4eb601 completed Aug. 18, 2026, 4:49 a.m.
NED2 Entity disambiguation (via description) batch_6a83e58835888190a5c9ad19e86eadd7 completed Aug. 18, 2026, 4:54 a.m.
Created at: May 3, 2026, 4:10 p.m.