Triple

T38625330
Position Surface form Disambiguated ID Type / Status
Subject SLQ E936989 entity
Predicate region P40 FINISHED
Object western Alaska
Western Alaska is a remote, sparsely populated part of the U.S. state of Alaska known for its rugged coastline, tundra landscapes, and predominantly Indigenous communities reliant on subsistence lifestyles.
E30198 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: western Alaska | Statement: [SLQ, region, western Alaska]
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: western Alaska
Triple: [SLQ, region, western Alaska]
Generated description
Western Alaska is a remote, sparsely populated part of the U.S. state of Alaska known for its rugged coastline, tundra landscapes, and predominantly Indigenous communities reliant on subsistence lifestyles.

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_69f76ed403208190b862dc795171353f completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd9969b7881908e6f2315a5468b14 completed May 7, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41fd56ae00819085f26cb8a50e9823 completed June 29, 2026, 5:06 a.m.
NEDg Description generation batch_6a41fe94c1fc8190bb21fee5acc371ff completed June 29, 2026, 5:11 a.m.
NED2 Entity disambiguation (via description) batch_6a41ff1ca2d481909286a6c77f64b8b1 completed June 29, 2026, 5:14 a.m.
Created at: May 3, 2026, 4:32 p.m.