Triple

T13856540
Position Surface form Disambiguated ID Type / Status
Subject Montlhéry E333079 entity
Predicate hasTwinTown P919 FINISHED
Object Schlitz E486414 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: Schlitz | Statement: [Montlhéry, hasTwinTown, Schlitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schlitz
Context triple: [Montlhéry, hasTwinTown, Schlitz]
  • A. Schlitz
    Schlitz is the surname of Don Schlitz, the American country music songwriter best known for penning hits like “The Gambler.”
  • B. Schlitz chosen
    Schlitz is a river in the German state of Hesse that flows through the town of Schlitz before joining the Werra.
  • C. Gambrinus Brewery
    Gambrinus Brewery is a major Czech brewery based in Plzeň, renowned for its traditional pale lagers and significant role in the country’s beer culture.
  • D. Budweis
    Budweis is the German name for České Budějovice, a historic city in the Czech Republic renowned for its brewing tradition and medieval architecture.
  • E. Pabst Brewing Company
    Pabst Brewing Company is a historic American brewery best known for producing Pabst Blue Ribbon and other classic beer brands.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02dc9f488190b7181dcb7e304632 completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0fb7c3c819081fc6f89aa17d6af completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.