Triple

T19869809
Position Surface form Disambiguated ID Type / Status
Subject B33 road E477482 entity
Predicate passesThrough P225 FINISHED
Object Bad Saulgau NE NERFINISHED

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: Bad Saulgau | Statement: [B33 road, passesThrough, Bad Saulgau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Saulgau
Context triple: [B33 road, passesThrough, Bad Saulgau]
  • A. Bad Saulgau chosen
    Bad Saulgau is a spa town in the district of Sigmaringen in Baden-Württemberg, Germany, known for its thermal baths and historic town center.
  • B. Lombach
    The Lombach is a small river in the Bernese Oberland region of Switzerland that flows through the municipality of Unterseen near Interlaken.
  • C. Sausheim
    Sausheim is a commune in the Haut-Rhin department of the Grand Est region in northeastern France, situated near the city of Mulhouse.
  • D. Willanzheim
    Willanzheim is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian wine-growing tradition.
  • E. Illzach
    Illzach is a commune in northeastern France’s Grand Est region, situated near the city of Mulhouse in the Haut-Rhin department.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e658a2cc8481908d134b0b5cf79d06 completed April 20, 2026, 4:47 p.m.
Created at: April 10, 2026, 1:51 p.m.