Triple

T16768274
Position Surface form Disambiguated ID Type / Status
Subject Alter Südfriedhof E407524 entity
Predicate ownedBy P347 FINISHED
Object City of Munich 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: City of Munich | Statement: [Alter Südfriedhof, ownedBy, City of Munich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Munich
Context triple: [Alter Südfriedhof, ownedBy, City of Munich]
  • 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. Munich
    "Munich" is a 2005 historical drama thriller film directed by Steven Spielberg that depicts the covert Israeli response to the 1972 Munich Olympics massacre.
  • C. Stadt Nürnberg
    Stadt Nürnberg is the municipal government of the German city of Nuremberg, responsible for local administration, public services, and urban infrastructure.
  • D. Munychia
    Munychia was a fortified hill and harbor district of ancient Athens, in Piraeus, known as the site where the oligarchic regime of the Thirty Tyrants was overthrown.
  • E. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b0349bc88190938750f1e5af192a completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2993f4c8190aecf29a4bcbf7b6a completed May 10, 2026, 5:38 p.m.
Created at: April 10, 2026, 5:21 a.m.