Triple

T37977409
Position Surface form Disambiguated ID Type / Status
Subject Southeastern Oklahoma E947460 entity
Predicate hasLandform P940 FINISHED
Object Kiamichi Mountains
The Kiamichi Mountains are a rugged, forested subrange of the Ouachita Mountains known for their scenic vistas, wildlife, and outdoor recreation opportunities in southeastern Oklahoma.
E57059 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: Kiamichi Mountains | Statement: [Southeastern Oklahoma, hasLandform, Kiamichi Mountains]
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: Kiamichi Mountains
Triple: [Southeastern Oklahoma, hasLandform, Kiamichi Mountains]
Generated description
The Kiamichi Mountains are a rugged, forested subrange of the Ouachita Mountains known for their scenic vistas, wildlife, and outdoor recreation opportunities in southeastern Oklahoma.

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_69f76ef7db908190bba6086673a32300 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbe1bc2f08190a6e2e5ba1273bd93 completed May 6, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41542df4348190a6c671950caf8328 completed June 28, 2026, 5:04 p.m.
NEDg Description generation batch_6a415797ba148190bfb1eb057b904a9f completed June 28, 2026, 5:19 p.m.
NED2 Entity disambiguation (via description) batch_6a4157eb7914819099c935c955acc3d1 completed June 28, 2026, 5:20 p.m.
Created at: May 3, 2026, 4:20 p.m.