Triple

T10082633
Position Surface form Disambiguated ID Type / Status
Subject Sömmerda district E213939 entity
Predicate contains P35 FINISHED
Object town of Sömmerda E722431 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: town of Sömmerda | Statement: [Sömmerda district, contains, town of Sömmerda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: town of Sömmerda
Context triple: [Sömmerda district, contains, town of Sömmerda]
  • A. Sömmerda chosen
    Sömmerda is a town in the German state of Thuringia, known historically for its industrial development and location on the Unstrut River.
  • B. Sömmerda district
    Sömmerda district is a rural administrative district (Landkreis) in the German state of Thuringia, known for its agricultural landscape and small towns north of Erfurt.
  • C. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • D. Frohnhausen
    Frohnhausen is a district (Ortsteil) of the town of Dillenburg in the Lahn-Dill-Kreis of Hesse, Germany.
  • E. Großjena
    Großjena is a village and district of the town of Naumburg in the German state of Saxony-Anhalt, known for its location in the Saale-Unstrut wine-growing region.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd03482d481908b03d35dc2d16395 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b66b256c8190861066f7c19008d2 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.