Triple

T3848806
Position Surface form Disambiguated ID Type / Status
Subject Berlin U-Bahn line U4 E85238 entity
Predicate runsEntirelyWithin P50003 FINISHED
Object Schöneberg area 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 area | Statement: [Berlin U-Bahn line U4, runsEntirelyWithin, Schöneberg area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schöneberg area
Context triple: [Berlin U-Bahn line U4, runsEntirelyWithin, Schöneberg area]
  • A. 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.
  • B. Bogenhausen district
    Bogenhausen district is an upscale residential and cultural area in Munich known for its historic villas, embassies, and prominent boulevards.
  • C. Nollendorfplatz area
    The Nollendorfplatz area is a lively Berlin neighborhood known for its historic square, vibrant LGBTQ+ scene, and mix of nightlife, cafés, and cultural venues.
  • D. 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.
  • E. Wannsee district
    Wannsee district is a lakeside area in southwestern Berlin known for its popular beaches, historic villas, and recreational waterfront attractions.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeebcde86081908cf3840ae002acfa completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5627ebbc48190914b663bab5e2a82 completed March 14, 2026, 1:28 p.m.
Created at: March 9, 2026, 3:19 p.m.