Triple

T13948825
Position Surface form Disambiguated ID Type / Status
Subject Walker County, Georgia E335461 entity
Predicate borders P224 FINISHED
Object Chattooga County, Georgia
Chattooga County, Georgia is a rural county in the northwestern part of the state known for its small towns, agricultural landscape, and location in the Appalachian foothills.
E1837476 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: Chattooga County, Georgia | Statement: [Walker County, Georgia, borders, Chattooga County, 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: Chattooga County, Georgia
Triple: [Walker County, Georgia, borders, Chattooga County, Georgia]
Generated description
Chattooga County, Georgia is a rural county in the northwestern part of the state known for its small towns, agricultural landscape, and location in the Appalachian foothills.

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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e12171c8190b95746bdd4845def completed April 14, 2026, 12:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bb70763c8190878e6ef716b6118a completed June 7, 2026, 12:29 a.m.
NEDg Description generation batch_6a24bfdddd108190b1f48a0317754806 completed June 7, 2026, 12:48 a.m.
NED2 Entity disambiguation (via description) batch_6a24c40832a881908ca8c2d0b09b1458 completed June 7, 2026, 1:06 a.m.
Created at: April 9, 2026, 10:17 p.m.