Triple

T14257406
Position Surface form Disambiguated ID Type / Status
Subject Mitte E353420 entity
Predicate contains P35 FINISHED
Object Alexanderplatz E136235 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: Alexanderplatz | Statement: [Mitte, contains, Alexanderplatz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alexanderplatz
Context triple: [Mitte, contains, Alexanderplatz]
  • A. Alexanderplatz chosen
    Alexanderplatz is a major public square and transport hub in central Berlin, known for its historic role in the city’s social and political life and its surrounding modernist architecture.
  • B. Martin-Luther-Platz
    Martin-Luther-Platz is a central square in Dresden’s Neustadt district, known for its historic urban setting and proximity to notable civic and religious buildings.
  • C. Marienplatz
    Marienplatz is the central square in Munich, Germany, renowned as the city's historic heart and a major hub for cultural events, tourism, and public life.
  • D. Leipziger Platz
    Leipziger Platz is a historic square in central Berlin, Germany, known for its reconstruction after German reunification and its proximity to Potsdamer Platz.
  • E. Luisenplatz
    Luisenplatz is the central square and main public plaza of Darmstadt, Germany, serving as a key hub for transportation, shopping, and civic life.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6352611c819090d062fe3079cd03 completed April 14, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd325f213881909acf776ff4831c30 completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:09 a.m.