Triple

T20483284
Position Surface form Disambiguated ID Type / Status
Subject Rupertiwinkel E502518 entity
Predicate containsSettlement P847 FINISHED
Object Teisendorf 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: Teisendorf | Statement: [Rupertiwinkel, containsSettlement, Teisendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teisendorf
Context triple: [Rupertiwinkel, containsSettlement, Teisendorf]
  • A. Teisendorf chosen
    Teisendorf is a market town in southeastern Bavaria, Germany, known for its rural Alpine setting and traditional Bavarian character.
  • B. Tattendorf
    Tattendorf is a small wine-growing village and municipality in Lower Austria, known for its vineyards and rural character.
  • C. Deutschendorf
    Deutschendorf is the original surname of American singer-songwriter and environmental activist John Denver, known for hits like "Take Me Home, Country Roads."
  • D. Biendorf
    Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
  • E. Heinersdorf
    Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
  • 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_69e0b4af32848190aea80682b44d5d6e completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69b58c4b4819083d0ba2397dbfb0b completed April 20, 2026, 9:32 p.m.
Created at: April 16, 2026, 11:34 a.m.