Triple

T14849531
Position Surface form Disambiguated ID Type / Status
Subject Gemeinsamer Bibliotheksverbund E349190 entity
Predicate headquartersLocation P62 FINISHED
Object Göttingen E25610 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 | Statement: [Gemeinsamer Bibliotheksverbund, headquartersLocation, Göttingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Göttingen
Context triple: [Gemeinsamer Bibliotheksverbund, headquartersLocation, Göttingen]
  • A. Göttingen chosen
    Göttingen is a historic university city in Lower Saxony, Germany, renowned for its prestigious Georg-August University and contributions to science and mathematics.
  • B. Heidberg
    Heidberg is a small locality or district that forms part of the town of Rüthen in North Rhine-Westphalia, Germany.
  • C. Darmstadt
    Darmstadt is a city in the German state of Hesse known for its historical ties to the Grand Duchy of Hesse and its role as a center of science, technology, and Art Nouveau culture.
  • D. Greifswald
    Greifswald is a historic Hanseatic university city in northeastern Germany, located near the Baltic Sea.
  • E. Heidelberg
    Heidelberg is a suburb of Melbourne, Australia, known for its historic role in Australian Impressionism and its location along the Yarra River.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded43eee188190bf24dc475b3abe28 completed April 14, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe8bc9db7c8190af08b26471d28e97 completed May 9, 2026, 1:20 a.m.
Created at: April 10, 2026, 1:54 a.m.