Triple

T1224322
Position Surface form Disambiguated ID Type / Status
Subject Berlin-Wannsee station E26291 entity
Predicate servesArea P82 FINISHED
Object Wannsee district E137768 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: Wannsee district | Statement: [Berlin-Wannsee station, servesArea, Wannsee district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wannsee district
Context triple: [Berlin-Wannsee station, servesArea, Wannsee district]
  • A. Wannsee district chosen
    Wannsee district is a lakeside area in southwestern Berlin known for its popular beaches, historic villas, and recreational waterfront attractions.
  • B. Babelsberg district
    Babelsberg district is a historic quarter of Potsdam, Germany, known for its film studios, lakeside villas, and well-preserved 19th- and early 20th-century architecture.
  • C. Alt-Mariendorf
    Alt-Mariendorf is a Berlin U-Bahn station in the Mariendorf district that serves as the southern terminus of line U6.
  • D. Sachsenhausen
    Sachsenhausen is a historic and culturally vibrant district of Frankfurt am Main, known for its traditional apple wine taverns, museums, and picturesque old town streets.
  • E. Schöneberg
    Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be233fd88190996faf4105c0b8d7 completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd46eefa48190baebc12fdf916941 completed March 8, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:47 p.m.