Triple

T20890420
Position Surface form Disambiguated ID Type / Status
Subject Zweibund E514393 entity
Predicate hasGermanName P1435 FINISHED
Object Zweibund NE NERFINISHED

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: Zweibund | Statement: [Zweibund, hasGermanName, Zweibund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zweibund
Context triple: [Zweibund, hasGermanName, Zweibund]
  • A. Zweibund chosen
    Zweibund was the German term for the Dual Alliance, a key late 19th-century military and political alliance between Germany and Austria-Hungary that shaped pre–World War I European diplomacy.
  • B. ZWEI
    ZWEI is an early extensible text editor developed at MIT, notable as a precursor and influence on later Emacs implementations.
  • C. Zwiefalten
    Zwiefalten is a small historic town and former monastic center in the state of Baden-Württemberg in southern Germany.
  • D. Gemena
    Gemena is a city in the northwestern part of the Democratic Republic of the Congo that serves as an important regional administrative and commercial center.
  • E. Zwiggelte
    Zwiggelte is a small village in the Dutch province of Drenthe, known for its rural character and agricultural surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4f7ebe48190952a85547a0f31a1 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6d05d591481908c9c999db76760fc completed April 21, 2026, 1:18 a.m.
Created at: April 16, 2026, 12:46 p.m.