Triple

T3270802
Position Surface form Disambiguated ID Type / Status
Subject BMW i8 E68641 entity
Predicate assembly P19323 FINISHED
Object Leipzig, Germany 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, Germany | Statement: [BMW i8, assembly, Leipzig, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leipzig, Germany
Context triple: [BMW i8, assembly, Leipzig, Germany]
  • 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. Torgau, Germany
    Torgau, Germany is a historic town in Saxony on the Elbe River, known for its Renaissance architecture and its role as a key site in the Protestant Reformation.
  • C. Brunswick, Germany
    Brunswick, Germany is a historic city in Lower Saxony known for its medieval architecture, former status as a ducal residence, and role as an important commercial and cultural center in northern Germany.
  • D. Giessen, Germany
    Giessen, Germany is a central German university town in the state of Hesse, known for its large student population and academic institutions.
  • E. 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.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adaff349148190beae8c0994b7ad83 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28f02a620819091356c965b2aceef completed March 12, 2026, 10:01 a.m.
Created at: March 8, 2026, 3:09 p.m.