Triple

T5284597
Position Surface form Disambiguated ID Type / Status
Subject Bezirk Gera E119584 entity
Predicate urbanDistrict P12103 FINISHED
Object Gera (Stadtkreis) E35113 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 (Stadtkreis) | Statement: [Bezirk Gera, urbanDistrict, Gera (Stadtkreis)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gera (Stadtkreis)
Context triple: [Bezirk Gera, urbanDistrict, Gera (Stadtkreis)]
  • A. Altstadt Gera
    Altstadt Gera is the historic old town district of Gera, Germany, characterized by preserved architecture, traditional squares, and cultural landmarks reflecting the city’s past.
  • B. Bezirk Gera
    Bezirk Gera was an administrative district of the former East Germany, centered around the city of Gera in the state of Thuringia.
  • C. Groß-Gerau district
    Groß-Gerau district is an administrative district in the German state of Hesse, located in the southern part of the Rhine-Main metropolitan region.
  • D. City of Gera chosen
    The City of Gera is a medium-sized city in the German state of Thuringia, historically known as an industrial and cultural center in eastern Germany.
  • E. Giessen district
    Giessen district is an administrative district in the German state of Hesse, centered around the city of Gießen and known for its mix of urban areas, universities, and rural landscapes.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84d693288190b437955e40ad6abb completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06e6200881908da623e8548ec051 completed March 21, 2026, 9 p.m.
Created at: March 20, 2026, 1:52 p.m.