Triple

T27820013
Position Surface form Disambiguated ID Type / Status
Subject Valser mineral water E702786 entity
Predicate brandName P1500 FINISHED
Object Valser
Valser is a Swiss brand of mineral water sourced from alpine springs and known for its naturally carbonated and still varieties.
E1791398 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: Valser | Statement: [Valser mineral water, brandName, Valser]
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: Valser
Triple: [Valser mineral water, brandName, Valser]
Generated description
Valser is a Swiss brand of mineral water sourced from alpine springs and known for its naturally carbonated and still varieties.

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_69ef840ad1e88190b5bff2d1ddec8700 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6386d6808819090f7db4b6a028698 completed May 2, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f72576f08190baff24d7a71eb859 completed May 24, 2026, 1:03 p.m.
NEDg Description generation batch_6a12f7d3b7048190ae5778d0d22bfd77 completed May 24, 2026, 1:06 p.m.
NED2 Entity disambiguation (via description) batch_6a12fbae881c8190a13234bf6ad26f8f completed May 24, 2026, 1:22 p.m.
Created at: April 27, 2026, 5:48 p.m.