Triple

T20280712
Position Surface form Disambiguated ID Type / Status
Subject Uvalde County E503132 entity
Predicate borderedByCounty P6346 FINISHED
Object Kinney County
Kinney County is a sparsely populated county in southwest Texas known for its ranching lands, border location near Mexico, and the historic town of Brackettville.
E2292764 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: Kinney County | Statement: [Uvalde County, borderedByCounty, Kinney County]
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: Kinney County
Triple: [Uvalde County, borderedByCounty, Kinney County]
Generated description
Kinney County is a sparsely populated county in southwest Texas known for its ranching lands, border location near Mexico, and the historic town of Brackettville.

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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6768e9f0881909c8fe8772dafd468 completed April 20, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a1ef9b2fc819095a4e7dc2a4d789b completed Aug. 10, 2026, 6:56 p.m.
NEDg Description generation batch_6a7a1fc527cc81909994b786fb21c1d2 completed Aug. 10, 2026, 7 p.m.
NED2 Entity disambiguation (via description) batch_6a7a20958de481909d41f9a1bee9f738 completed Aug. 10, 2026, 7:03 p.m.
Created at: April 16, 2026, 10:38 a.m.