Triple

T14755490
Position Surface form Disambiguated ID Type / Status
Subject Kohlmarkt E346718 entity
Predicate near P350 FINISHED
Object Michaelerkirche E938531 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: Michaelerkirche | Statement: [Kohlmarkt, near, Michaelerkirche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michaelerkirche
Context triple: [Kohlmarkt, near, Michaelerkirche]
  • A. Michaelerkirche chosen
    Michaelerkirche is a historic Roman Catholic church in the Austrian city of Steyr, noted for its prominent architecture and cultural significance.
  • B. Marienkirche
    Marienkirche is a historic medieval church in central Berlin, known as one of the city’s oldest surviving churches and a notable example of Brick Gothic architecture.
  • C. Marienkirche
    Marienkirche is a historic St. Mary’s Church located in the German town of Mühlhausen, known for its Gothic architecture and cultural significance.
  • D. Marienkirche
    Marienkirche is a historic church in the German town of Wolfenbüttel, notable for its architectural and cultural significance.
  • E. Liebfrauenkirche
    Liebfrauenkirche is a prominent historic Catholic church in Ravensburg, Germany, noted for its distinctive tower and late Gothic architecture.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7ef0fd48190bd4a8af128ef274c completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24afff788190ab4925ead7ce90d2 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:30 a.m.