Triple

T3688050
Position Surface form Disambiguated ID Type / Status
Subject Mulde E78272 entity
Predicate crossesAdministrativeRegion P13729 FINISHED
Object Dessau-Roßlau urban district E53961 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: Dessau-Roßlau urban district | Statement: [Mulde, crossesAdministrativeRegion, Dessau-Roßlau urban district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dessau-Roßlau urban district
Context triple: [Mulde, crossesAdministrativeRegion, Dessau-Roßlau urban district]
  • A. City of Dessau-Roßlau chosen
    The City of Dessau-Roßlau is a German city in Saxony-Anhalt known for its Bauhaus architectural heritage and role as an industrial and cultural center in central Germany.
  • B. Dessau
    Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
  • C. Degendorf
    Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
  • D. Babelsberg district
    Babelsberg district is a historic quarter of Potsdam, Germany, known for its film studios, lakeside villas, and well-preserved 19th- and early 20th-century architecture.
  • E. Lichterfelde
    Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent character.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4c960788190b73ede08658846aa completed March 8, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5282613d0819085a47d1fffdaa4d5 completed March 14, 2026, 9:19 a.m.
Created at: March 8, 2026, 3:26 p.m.