Triple

T23267301
Position Surface form Disambiguated ID Type / Status
Subject Mason County, West Virginia E588186 entity
Predicate hasCommunity P2605 FINISHED
Object Fraziers Bottom, West Virginia
Fraziers Bottom is an unincorporated rural community in Mason County, West Virginia, situated along the Kanawha River.
E1607676 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: Fraziers Bottom, West Virginia | Statement: [Mason County, West Virginia, hasCommunity, Fraziers Bottom, 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: Fraziers Bottom, West Virginia
Triple: [Mason County, West Virginia, hasCommunity, Fraziers Bottom, West Virginia]
Generated description
Fraziers Bottom is an unincorporated rural community in Mason County, West Virginia, situated along the Kanawha River.

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_69e25d148adc819088efbf42672604e9 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19570fcc0819091df22140828155b completed April 29, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f75e5abc48190ab4fc496446a6f26 completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f77372e188190bbf5c1a77de0833c completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77d47ea08190828e5f5f9f0e3899 completed May 21, 2026, 9:23 p.m.
Created at: April 17, 2026, 4:38 p.m.