Triple

T11665895
Position Surface form Disambiguated ID Type / Status
Subject Upper Saxon Circle E277244 entity
Predicate appliesToJurisdiction P82 FINISHED
Object City of Erfurt E281989 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: City of Erfurt | Statement: [Upper Saxon Circle, appliesToJurisdiction, City of Erfurt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Erfurt
Context triple: [Upper Saxon Circle, appliesToJurisdiction, City of Erfurt]
  • A. Erfurt chosen
    Erfurt is a historic German city in the state of Thuringia, known for its well-preserved medieval old town and as an important cultural and educational center.
  • B. 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.
  • C. Altdorf bei Nürnberg
    Altdorf bei Nürnberg is a small historic town in Bavaria, Germany, known for its former university and proximity to the city of Nuremberg.
  • D. Karlstadt am Main
    Karlstadt am Main is a historic town in northern Bavaria, Germany, situated on the River Main and known for its medieval old town and surrounding wine-growing region.
  • E. Riedenburg
    Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a43f438081909da476294a057c38 completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef82e252fc819082b5c8a33fcf861a completed April 27, 2026, 3:38 p.m.
Created at: April 8, 2026, 9:39 p.m.