Triple

T16759037
Position Surface form Disambiguated ID Type / Status
Subject Rathaus Schöneberg station E407289 entity
Predicate servesDistrict P82 FINISHED
Object Schöneberg E13289 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: Schöneberg | Statement: [Rathaus Schöneberg station, servesDistrict, Schöneberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schöneberg
Context triple: [Rathaus Schöneberg station, servesDistrict, Schöneberg]
  • A. Schöneberg chosen
    Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
  • B. Schönewalde
    Schönewalde is a town in the state of Brandenburg, Germany, known for hosting a German Air Force base.
  • C. Schönholz
    Schönholz is a locality in Berlin, Germany, served by the city’s S-Bahn rapid transit network.
  • D. Petershagen
    Petershagen is a small town in North Rhine-Westphalia, Germany, known for its historic architecture and scenic location along the Weser River.
  • E. Schönwalde
    Schönwalde is a locality within the municipality of Wandlitz in the state of Brandenburg, Germany.
  • 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_69e3abeb3ab08190918f6bff686858be completed April 18, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aaf7908481909af31fc2d02f33fb completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:21 a.m.