Triple

T937229
Position Surface form Disambiguated ID Type / Status
Subject Battle of Leipzig E20223 entity
Predicate location P40 FINISHED
Object Leipzig E38199 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 | Statement: [Battle of Leipzig, location, Leipzig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leipzig
Context triple: [Battle of Leipzig, location, Leipzig]
  • A. Leipzig chosen
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • B. Dresden
    Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
  • C. Magdeburg
    Magdeburg is a historic city in central Germany, known for its medieval cathedral, role as a major trading and industrial center, and location on the Elbe River.
  • D. Cottbus
    Cottbus is a city in eastern Germany known as a regional center for science and technology, including aerospace research.
  • E. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • 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_69a493b0270c81909e6c9ce310f6aa55 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3668a3c8190b0152166efa93ee1 completed March 1, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae7190fb84819095e6ebf2eeb50148 completed March 9, 2026, 7:06 a.m.
Created at: March 1, 2026, 7:40 p.m.