Triple

T8020363
Position Surface form Disambiguated ID Type / Status
Subject Unstrut River region E186724 entity
Predicate contains P35 FINISHED
Object Mühlhausen E351668 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: Mühlhausen | Statement: [Unstrut River region, contains, Mühlhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mühlhausen
Context triple: [Unstrut River region, contains, Mühlhausen]
  • A. Mühlhausen chosen
    Mühlhausen is a historic town in central Germany, known for its well-preserved medieval architecture and cultural heritage.
  • B. Markranstädt
    Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
  • C. Günzburg
    Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
  • D. Suhl
    Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
  • E. Eisenach
    Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
  • 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_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3e8d90488190b57d1e748e272061 completed March 31, 2026, 3:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd33f9074c8190aeefc7f5283017e9 completed April 1, 2026, 3:04 p.m.
Created at: March 30, 2026, 5:20 p.m.