Triple

T15493823
Position Surface form Disambiguated ID Type / Status
Subject Max-Weber-Platz U-Bahn station E378762 entity
Predicate servesDistrict P82 FINISHED
Object Au-Haidhausen E756954 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: Au-Haidhausen | Statement: [Max-Weber-Platz U-Bahn station, servesDistrict, Au-Haidhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Au-Haidhausen
Context triple: [Max-Weber-Platz U-Bahn station, servesDistrict, Au-Haidhausen]
  • A. Stadelhofen
    Stadelhofen is a village and district of the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
  • B. Haidhausen area
    The Haidhausen area is a historic and now trendy district of Munich known for its charming old buildings, lively cafés, and cultural venues along the Isar River.
  • C. Munich-Haidhausen chosen
    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. Giesing
    Giesing is a district in Munich, Germany, known as a historically working-class neighborhood that today combines residential areas with notable institutions such as the nearby Stadelheim Prison.
  • E. Bockenheim
    Bockenheim is a lively urban district of Frankfurt am Main known for its mix of residential areas, shops, and university facilities.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fad723481908d2aa33e8f065f2f completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c345f888190be7a684f3bd86324 completed May 9, 2026, 3:01 p.m.
Created at: April 10, 2026, 3:49 a.m.