Triple

T28765059
Position Surface form Disambiguated ID Type / Status
Subject Zervreila reservoir E726243 entity
Predicate watercourse P415 FINISHED
Object Valserrhein
Valserrhein is a river in the canton of Graubünden in Switzerland that drains the Vals Valley and feeds into the Rhine system.
E1878458 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: Valserrhein | Statement: [Zervreila reservoir, watercourse, Valserrhein]
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: Valserrhein
Triple: [Zervreila reservoir, watercourse, Valserrhein]
Generated description
Valserrhein is a river in the canton of Graubünden in Switzerland that drains the Vals Valley and feeds into the Rhine system.

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_69f03198be14819098fa74e48b3749bf completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f65823570c8190a4cbfb7a4c732e87 completed May 2, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a267e8fb0588190ad968db97c1281a2 completed June 8, 2026, 8:34 a.m.
NEDg Description generation batch_6a26829c7dd08190bb73080b8b53a01f completed June 8, 2026, 8:51 a.m.
NED2 Entity disambiguation (via description) batch_6a2686a5e49481909dbbfb8ef71556bd completed June 8, 2026, 9:08 a.m.
Created at: April 28, 2026, 6:13 a.m.