Triple

T2238092
Position Surface form Disambiguated ID Type / Status
Subject Suebi E49327 entity
Predicate influencedToponym P20713 FINISHED
Object Schwaben E64457 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: Schwaben | Statement: [Suebi, influencedToponym, Schwaben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwaben
Context triple: [Suebi, influencedToponym, Schwaben]
  • A. Swabia (Bavaria) chosen
    Swabia (Bavaria) is an administrative region in southwestern Bavaria, Germany, known for its distinct Swabian cultural heritage and mix of industrial cities and rural landscapes.
  • B. Moravia
    Moravia is a historical region in the eastern part of the Czech Republic, known for its distinct cultural heritage, wine production, and major cities such as Brno and Olomouc.
  • C. Sorbs
    The Sorbs are a Slavic ethnic minority primarily living in eastern Germany, known for preserving their distinct Sorbian language and cultural traditions.
  • D. Banat Swabians
    Banat Swabians are an ethnic German community historically settled in the Banat region of Central and Eastern Europe, primarily in present-day Romania and Serbia.
  • E. Styria
    Styria is a federal state in southeastern Austria known for its capital Graz, diverse landscapes, and strong industrial and educational sectors.
  • 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_69a88aa84bdc819086df50e9c20b301e completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc5b262488190b6455d1d28d2306d completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b0a9ee881909dee8b0a657b9c73 completed March 9, 2026, 6:39 a.m.
Created at: March 4, 2026, 7:47 p.m.