Triple

T27810990
Position Surface form Disambiguated ID Type / Status
Subject Ronto Roasters E702517 entity
Predicate diningType P9631 FINISHED
Object counter service LITERAL FINISHED

How this triple was built (1 step)

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: counter service | Statement: [Ronto Roasters, diningType, counter service]

Provenance (2 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_69ef840a16748190926719ab96120bae completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6383e63288190a7d5b06acef39665 completed May 2, 2026, 5:45 p.m.
Created at: April 27, 2026, 5:42 p.m.