Triple

T1595808
Position Surface form Disambiguated ID Type / Status
Subject Tver E34278 entity
Predicate twinnedWith P1072 FINISHED
Object Gera E22181 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: Gera | Statement: [Tver, twinnedWith, Gera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gera
Context triple: [Tver, twinnedWith, Gera]
  • A. Gera chosen
    Gera is a city in the German state of Thuringia, known for its industrial heritage and historic architecture along the White Elster river.
  • B. Morava
    Morava is a Central European river that forms part of the border between Austria, the Czech Republic, and Slovakia before joining the Danube near Bratislava.
  • C. Lahn
    The Lahn is a river in western Germany that flows through the states of North Rhine-Westphalia, Hesse, and Rhineland-Palatinate before joining the Rhine.
  • D. Werre
    The Werre is a river in North Rhine-Westphalia, Germany, that flows through towns such as Detmold and Herford before joining the Weser.
  • E. Schwabach
    Schwabach is a historic town in northern Bavaria, Germany, known for its traditional gold-beating craft and well-preserved old town.
  • 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_69a885fdcb9c819081ce6f0b8cd477dd completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9092ccb388190b2f3ed86b3853651 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58c1d9ac819085e497b630a99d96 completed March 8, 2026, 11:08 a.m.
Created at: March 4, 2026, 7:27 p.m.