Triple

T25816340
Position Surface form Disambiguated ID Type / Status
Subject Caribou Lakes E650265 entity
Predicate region P40 FINISHED
Object Northern Sierra–Klamath area
The Northern Sierra–Klamath area is a mountainous region of northern California known for its rugged terrain, extensive forests, and numerous alpine lakes and wilderness areas.
 E1702169 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: Northern Sierra–Klamath area | Statement: [Caribou Lakes, region, Northern Sierra–Klamath area]
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: Northern Sierra–Klamath area
Triple: [Caribou Lakes, region, Northern Sierra–Klamath area]
Generated description
The Northern Sierra–Klamath area is a mountainous region of northern California known for its rugged terrain, extensive forests, and numerous alpine lakes and wilderness areas.

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_69e7ab367fcc8190a5ff1e7f3da046a4 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f600c915908190aea4b20f6b9b11b6 completed May 2, 2026, 1:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10eca63c588190a76afa281a1cee55 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10eddf8e008190a604d8c0db0fdd9d completed May 22, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_6a10efe2fc188190ab9d5e8276a1ef2f completed May 23, 2026, 12:08 a.m.
Created at: April 22, 2026, 7:26 a.m.