Triple

T8729425
Position Surface form Disambiguated ID Type / Status
Subject Bruno Walter E207214 entity
Predicate employer P7 FINISHED
Object Leipzig Opera E200405 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: Leipzig Opera | Statement: [Bruno Walter, employer, Leipzig Opera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leipzig Opera
Context triple: [Bruno Walter, employer, Leipzig Opera]
  • A. Leipzig Opera chosen
    Leipzig Opera is one of Germany’s oldest opera houses, renowned for its rich musical tradition and historic role in the development of European opera.
  • B. Sächsische Staatsoper Dresden
    The Sächsische Staatsoper Dresden is a renowned German opera company based in Dresden’s historic Semperoper, celebrated for its rich tradition and close ties to the Staatskapelle Dresden orchestra.
  • C. Hamburg State Opera
    Hamburg State Opera is a major German opera company and historic cultural institution in Hamburg, renowned for its world-class productions and leading international artists.
  • D. Deutsche Oper Berlin
    Deutsche Oper Berlin is one of Germany’s largest and most renowned opera houses, known for its grand productions and modernist architecture in Berlin.
  • E. Berlin State Opera
    The Berlin State Opera is one of Germany’s leading opera houses, renowned for its historic venue, world-class productions, and prominent role in Berlin’s cultural life.
  • 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_69ca8358e4008190898471a59b96c301 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d19fdc88190860e0c9c93ab79ce completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf5174db7881908597d5dc472adde9 completed April 3, 2026, 5:34 a.m.
Created at: March 30, 2026, 6:37 p.m.