Triple

T31736787
Position Surface form Disambiguated ID Type / Status
Subject Virginia State Route 762 E810020 entity
Predicate routeDesignation P1864 FINISHED
Object State Route 762
State Route 762 is a secondary state highway designation used for various local roads within the Commonwealth of Virginia’s state route system.
 E2295790 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 762 | Statement: [Virginia State Route 762, routeDesignation, State Route 762]
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 762
Triple: [Virginia State Route 762, routeDesignation, State Route 762]
Generated description
State Route 762 is a secondary state highway designation used for various local roads within the Commonwealth of Virginia’s state route system.

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_69f348e0e4908190a884582eca646fb7 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6ab23f4608190ace81412a377eff8 completed May 3, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a81f3a00f7481908343264baaebce7a completed Aug. 16, 2026, 5:30 p.m.
NEDg Description generation batch_6a81f40424808190bf4840e1a89af957 completed Aug. 16, 2026, 5:31 p.m.
NED2 Entity disambiguation (via description) batch_6a81f4566c688190acf962a8fc8fa703 completed Aug. 16, 2026, 5:33 p.m.
Created at: April 30, 2026, 11:23 p.m.