Triple

T26165878
Position Surface form Disambiguated ID Type / Status
Subject Dolly Varden trout E654249 entity
Predicate genus P87 FINISHED
Object Salvelinus
Salvelinus is a genus of cold-water salmonid fish that includes chars such as brook trout, lake trout, and Arctic char.
E1713318 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: Salvelinus | Statement: [Dolly Varden trout, genus, Salvelinus]
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: Salvelinus
Triple: [Dolly Varden trout, genus, Salvelinus]
Generated description
Salvelinus is a genus of cold-water salmonid fish that includes chars such as brook trout, lake trout, and Arctic char.

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_69ee5b44391c81908bdbd8813ba9aa99 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60c3f0f7c8190b30ecf9e77e8dd5a completed May 2, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118571e87c819098f59533961221f5 completed May 23, 2026, 10:46 a.m.
NEDg Description generation batch_6a11861e622c8190a73ab247d696435a completed May 23, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a1186c04c2c8190a5e70c9d9a5cbeb8 completed May 23, 2026, 10:51 a.m.
Created at: April 26, 2026, 8:32 p.m.