Triple

T8066196
Position Surface form Disambiguated ID Type / Status
Subject District of Mittelsachsen E188248 entity
Predicate contains P35 FINISHED
Object Mittweida
Mittweida is a small town in the German state of Saxony, known for its university of applied sciences and historic architecture.
E722461 NE FINISHED

How this triple was built (4 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: Mittweida | Statement: [District of Mittelsachsen, contains, Mittweida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mittweida
Context triple: [District of Mittelsachsen, contains, Mittweida]
  • A. Seiffen
    Seiffen is a village in Germany’s Ore Mountains renowned for its traditional wooden toy-making and iconic Christmas decorations.
  • B. Weitra
    Weitra is a historic small town in Lower Austria known for its medieval architecture and one of the oldest breweries in Austria.
  • C. Dinkelsbühl
    Dinkelsbühl is a well-preserved medieval town in Bavaria, Germany, renowned for its intact city walls, historic half-timbered houses, and picturesque old town.
  • D. Brünnlitz
    Brünnlitz is a village in the Czech Republic best known as the location of Oskar Schindler’s wartime factory where he employed and saved Jewish workers during the Holocaust.
  • E. Vöcklabruck
    Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mittweida
Triple: [District of Mittelsachsen, contains, Mittweida]
Generated description
Mittweida is a small town in the German state of Saxony, known for its university of applied sciences and historic architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mittweida
Target entity description: Mittweida is a small town in the German state of Saxony, known for its university of applied sciences and historic architecture.
  • A. Seiffen
    Seiffen is a village in Germany’s Ore Mountains renowned for its traditional wooden toy-making and iconic Christmas decorations.
  • B. Weitra
    Weitra is a historic small town in Lower Austria known for its medieval architecture and one of the oldest breweries in Austria.
  • C. Dinkelsbühl
    Dinkelsbühl is a well-preserved medieval town in Bavaria, Germany, renowned for its intact city walls, historic half-timbered houses, and picturesque old town.
  • D. Brünnlitz
    Brünnlitz is a village in the Czech Republic best known as the location of Oskar Schindler’s wartime factory where he employed and saved Jewish workers during the Holocaust.
  • E. Vöcklabruck
    Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
  • F. None of above. chosen

Provenance (5 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_69ca82b42674819086840efea12478e5 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ff5547c8190a7ec5958a23e302f completed March 31, 2026, 3:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd6769c6948190805188b09c16bed4 completed April 1, 2026, 6:43 p.m.
NEDg Description generation batch_69cd6d4fa17481909f28ad7eb9bceb42 completed April 1, 2026, 7:09 p.m.
NED2 Entity disambiguation (via description) batch_69cd7da4f3a0819080eed3d03c293789 completed April 1, 2026, 8:18 p.m.
Created at: March 30, 2026, 5:26 p.m.