Triple

T30311754
Position Surface form Disambiguated ID Type / Status
Subject U.S. Highways in West Virginia E770943 entity
Predicate hasRoute P4374 FINISHED
Object U.S. Route 60 in West Virginia
U.S. Route 60 in West Virginia is a major east–west highway that traverses the state, connecting key cities and towns while roughly paralleling the Kanawha and New Rivers.
E1913746 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 60 in West Virginia | Statement: [U.S. Highways in West Virginia, hasRoute, U.S. Route 60 in West Virginia]
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 60 in West Virginia
Triple: [U.S. Highways in West Virginia, hasRoute, U.S. Route 60 in West Virginia]
Generated description
U.S. Route 60 in West Virginia is a major east–west highway that traverses the state, connecting key cities and towns while roughly paralleling the Kanawha and New Rivers.

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_69f22488f224819081b0f3ec41ab975c completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6816c17e08190b543186d578dca88 completed May 2, 2026, 10:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27892ec94c8190a0fa96065f14416f completed June 9, 2026, 3:31 a.m.
NEDg Description generation batch_6a278b1a81148190b6817cb1c3ddc976 completed June 9, 2026, 3:40 a.m.
NED2 Entity disambiguation (via description) batch_6a278bc71d4c81908564434ab6309540 completed June 9, 2026, 3:43 a.m.
Created at: April 29, 2026, 7:50 p.m.