Triple

T8328394
Position Surface form Disambiguated ID Type / Status
Subject Allerheiligen-Hofkirche E195013 entity
Predicate locatedIn P40 FINISHED
Object Altstadt-Lehel E206869 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: Altstadt-Lehel | Statement: [Allerheiligen-Hofkirche, locatedIn, Altstadt-Lehel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Altstadt-Lehel
Context triple: [Allerheiligen-Hofkirche, locatedIn, Altstadt-Lehel]
  • A. Altstadt-Lehel borough chosen
    Altstadt-Lehel is a central Munich borough that encompasses the historic Old Town and some of the city’s most prominent cultural and architectural landmarks.
  • B. Bockenheim
    Bockenheim is a lively urban district of Frankfurt am Main known for its mix of residential areas, shops, and university facilities.
  • C. Altstadt
    Altstadt is the historic old town of Zürich, Switzerland, known for its medieval streets, preserved architecture, and cultural landmarks along the Limmat River.
  • D. Altstadt
    Altstadt is the historic old town district of Dresden, Germany, known for its baroque architecture and major cultural landmarks.
  • E. Altstadt
    Altstadt is the historic old town district of Höchst, characterized by its preserved medieval architecture and traditional charm.
  • 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_69ca82e87f2c8190bdb71ee29dfc642d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f8243288190b1ae74d69395fc91 completed March 31, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95c2c36481909793e9cd0c28168a completed April 1, 2026, 10:01 p.m.
Created at: March 30, 2026, 5:56 p.m.