Triple

T33581609
Position Surface form Disambiguated ID Type / Status
Subject U.S. Highways in Georgia E860162 entity
Predicate hasRoute P4374 FINISHED
Object U.S. Route 278 in Georgia
U.S. Route 278 in Georgia is a major east–west U.S. Highway that traverses the state, connecting cities such as Atlanta and Augusta while serving as an important regional transportation corridor.
E2061045 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: U.S. Route 278 in Georgia | Statement: [U.S. Highways in Georgia, hasRoute, U.S. Route 278 in Georgia]
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: U.S. Route 278 in Georgia
Triple: [U.S. Highways in Georgia, hasRoute, U.S. Route 278 in Georgia]
Generated description
U.S. Route 278 in Georgia is a major east–west U.S. Highway that traverses the state, connecting cities such as Atlanta and Augusta while serving as an important regional transportation corridor.

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_69f3497d37848190afcbb5ef3f5c7376 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f7703d988190aa80bc5300b3a958 completed May 3, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36270c53f48190aa1b8290e7bd9465 completed June 20, 2026, 5:37 a.m.
NEDg Description generation batch_6a3628077de08190af490293002fb49d completed June 20, 2026, 5:41 a.m.
NED2 Entity disambiguation (via description) batch_6a36290ab68081908c16a32eac142a8d completed June 20, 2026, 5:45 a.m.
Created at: May 1, 2026, 1:40 a.m.