Triple

T35586750
Position Surface form Disambiguated ID Type / Status
Subject Glaciers of Snohomish County, Washington E1028378 entity
Predicate hasPart P35 FINISHED
Object Lyman Glacier
Lyman Glacier is a mountain glacier in the North Cascades of Washington State, known for its scenic alpine setting and contribution to local watershed systems.
E2289982 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: Lyman Glacier | Statement: [Glaciers of Snohomish County, Washington, hasPart, Lyman Glacier]
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: Lyman Glacier
Triple: [Glaciers of Snohomish County, Washington, hasPart, Lyman Glacier]
Generated description
Lyman Glacier is a mountain glacier in the North Cascades of Washington State, known for its scenic alpine setting and contribution to local watershed systems.

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_69f76e0495a081909beced418558c0b4 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79e8829ac8190aa340c57132219dd completed May 3, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5b846a80588190b1eaa4bdc0961e0c completed July 18, 2026, 1:49 p.m.
NEDg Description generation batch_6a5b849d740881909c344c7bfe3959f2 completed July 18, 2026, 1:50 p.m.
NED2 Entity disambiguation (via description) batch_6a5b85eb39d88190a95f95d1ec958c74 completed July 18, 2026, 1:55 p.m.
Created at: May 3, 2026, 4:04 p.m.