Triple

T3678038
Position Surface form Disambiguated ID Type / Status
Subject Mitte, Hanover E78042 entity
Predicate hasLandmark P105 FINISHED
Object Hanover Central Station E118890 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: Hanover Central Station | Statement: [Mitte, Hanover, hasLandmark, Hanover Central Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanover Central Station
Context triple: [Mitte, Hanover, hasLandmark, Hanover Central Station]
  • A. Hannover Hauptbahnhof chosen
    Hannover Hauptbahnhof is the main central railway station of Hanover, Germany, serving as a major national and international transport hub.
  • B. Bern Hauptbahnhof
    Bern Hauptbahnhof is the main railway station in Switzerland’s capital city, serving as a major national and international transport hub.
  • C. Eidelstedt station
    Eidelstedt station is a railway and S-Bahn station in the Eidelstedt district of Hamburg, Germany, serving as a local and regional transport hub.
  • D. Braunschweig Hauptbahnhof
    Braunschweig Hauptbahnhof is the main railway station and central transportation hub of the city of Braunschweig in Lower Saxony, Germany.
  • E. Berlin Station
    Berlin Station is an American espionage drama television series that follows CIA officers operating out of the agency’s Berlin branch as they navigate complex political and intelligence conflicts.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc46599188190a046eddb0d85c483 completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3a50d40819081aad0c72bcaee9d completed March 14, 2026, 2:10 a.m.
Created at: March 8, 2026, 3:25 p.m.