Triple

T3638297
Position Surface form Disambiguated ID Type / Status
Subject Prinzregentenstraße, Munich E77123 entity
Predicate partOf P40 FINISHED
Object Altstadt-Lehel district 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 district | Statement: [Prinzregentenstraße, Munich, partOf, Altstadt-Lehel district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Altstadt-Lehel district
Context triple: [Prinzregentenstraße, Munich, partOf, Altstadt-Lehel district]
  • 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. Bogenhausen district
    Bogenhausen district is an upscale residential and cultural area in Munich known for its historic villas, embassies, and prominent boulevards.
  • C. Dorotheenstadt
    Dorotheenstadt is a historic district in central Berlin, Germany, known for its cultural significance and notable institutions.
  • D. Wannsee district
    Wannsee district is a lakeside area in southwestern Berlin known for its popular beaches, historic villas, and recreational waterfront attractions.
  • E. Vaihingen district
    Vaihingen district is a borough of Stuttgart, Germany, known for its mix of residential areas, commercial zones, and several U.S. military 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_69ad85dd0be48190b738990cb20c4731 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc32a5d448190b24f379b8b2d4f9b completed March 8, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b488320c58819088f8cc677f675ec3 completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:24 p.m.