Triple

T8929971
Position Surface form Disambiguated ID Type / Status
Subject MAN Truck & Bus E212627 entity
Predicate headquartersLocation P62 FINISHED
Object Munich, Germany E21335 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: Munich, Germany | Statement: [MAN Truck & Bus, headquartersLocation, Munich, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munich, Germany
Context triple: [MAN Truck & Bus, headquartersLocation, Munich, Germany]
  • A. Munich chosen
    Munich is the capital and largest city of the German state of Bavaria, renowned for its rich cultural scene, historic architecture, and the annual Oktoberfest beer festival.
  • B. Leverkusen
    Leverkusen is a city in western Germany, known for its chemical industry and as the home of the football club Bayer 04 Leverkusen.
  • C. Munich-Haidhausen
    Munich-Haidhausen is a historic and centrally located district of Munich known for its charming old streets, vibrant cultural scene, and mix of residential and governmental buildings.
  • D. 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.
  • E. Deggendorf, Germany
    Deggendorf, Germany is a Bavarian town on the Danube River known as a regional commercial and industrial center with strong ties to manufacturing and technology companies.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6676d5d881908ce78cbb5561a68b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb856560819085132abe9ef94819 completed April 3, 2026, 3:23 p.m.
Created at: March 30, 2026, 6:57 p.m.