Triple

T8652974
Position Surface form Disambiguated ID Type / Status
Subject Porsche Cayenne E205143 entity
Predicate assemblyLocation P40 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: [Porsche Cayenne, assemblyLocation, Leipzig, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leipzig, Germany
Context triple: [Porsche Cayenne, assemblyLocation, 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. Brühl, Germany
    Brühl, Germany is a town in North Rhine-Westphalia known for its UNESCO-listed Augustusburg and Falkenlust palaces and its proximity to Cologne.
  • C. Linden, Germany
    Linden, Germany is a small town in the state of Hesse known for its historical roots and traditional German character.
  • D. 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.
  • E. 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.
  • 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_69ca834e56848190abb0eeaec9dedd32 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc484206d881908017897dada63124 completed March 31, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef368f6f081908dcfa2f28e476b02 completed April 2, 2026, 10:53 p.m.
Created at: March 30, 2026, 6:29 p.m.