Triple

T36881845
Position Surface form Disambiguated ID Type / Status
Subject Wayne County, West Virginia E911499 entity
Predicate hasSettlement P1068 FINISHED
Object Lavalette, West Virginia
Lavalette, West Virginia is a small unincorporated community and suburb of Huntington located in Wayne County in the western part of the state.
E2202758 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: Lavalette, West Virginia | Statement: [Wayne County, West Virginia, hasSettlement, Lavalette, 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: Lavalette, West Virginia
Triple: [Wayne County, West Virginia, hasSettlement, Lavalette, West Virginia]
Generated description
Lavalette, West Virginia is a small unincorporated community and suburb of Huntington located in Wayne County in the western part of the state.

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_69f76e82339881909607a65c0503d941 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fd6aba048190b23406b692bbf9fa completed May 5, 2026, 2:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfaedb3388190bb3cdfd4bab08277 completed June 26, 2026, 4:07 a.m.
NEDg Description generation batch_6a3e020a7cd4819091f3e7c702115131 completed June 26, 2026, 4:37 a.m.
NED2 Entity disambiguation (via description) batch_6a3e0472733081908c285234143df57a completed June 26, 2026, 4:47 a.m.
Created at: May 3, 2026, 4:13 p.m.