Triple

T1193313
Position Surface form Disambiguated ID Type / Status
Subject Göttingen E25610 entity
Predicate hasRailwayStation P918 FINISHED
Object Göttingen railway station E43143 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: Göttingen railway station | Statement: [Göttingen, hasRailwayStation, Göttingen railway station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Göttingen railway station
Context triple: [Göttingen, hasRailwayStation, Göttingen railway station]
  • A. Göttingen railway station chosen
    Göttingen railway station is a major rail hub in Lower Saxony, Germany, serving as an important stop on the country’s high-speed and regional rail networks.
  • B. Gera Hauptbahnhof
    Gera Hauptbahnhof is the main railway station and central transport hub of the city of Gera in Thuringia, Germany.
  • C. Hannover Hauptbahnhof
    Hannover Hauptbahnhof is the main central railway station of Hanover, Germany, serving as a major national and international transport hub.
  • D. Nürnberg Hauptbahnhof
    Nürnberg Hauptbahnhof is the main railway station and a central public transport hub in Nuremberg, Germany, serving regional, long-distance, and urban transit including the U-Bahn network.
  • E. Bern Hauptbahnhof
    Bern Hauptbahnhof is the main railway station in Switzerland’s capital city, serving as a major national and international transport hub.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd761ef08190b431b80f326d1ab2 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac764ea588819082f7d5d0e44e1211 completed March 7, 2026, 7:02 p.m.
Created at: March 1, 2026, 7:46 p.m.