Triple

T19598171
Position Surface form Disambiguated ID Type / Status
Subject Julius Kühn Institute E470400 entity
Predicate headquartersLocation P62 FINISHED
Object Quedlinburg NE NERFINISHED

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: Quedlinburg | Statement: [Julius Kühn Institute, headquartersLocation, Quedlinburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quedlinburg
Context triple: [Julius Kühn Institute, headquartersLocation, Quedlinburg]
  • A. Quedlinburg chosen
    Quedlinburg is a historic German town on the northern edge of the Harz mountains, renowned for its well-preserved medieval architecture and UNESCO World Heritage–listed old town.
  • B. Halberstadt
    Halberstadt is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and role as a former episcopal seat.
  • C. Wolfenbüttel
    Wolfenbüttel is a historic town in Lower Saxony, Germany, known for its Renaissance castle and rich cultural heritage.
  • D. Malching
    Malching is a small municipality in southeastern Bavaria, Germany, situated near the Austrian border in the district of Passau.
  • E. Querfurt
    Querfurt is a small historic town in the German state of Saxony-Anhalt, known for its well-preserved medieval castle and old town.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6407c52c081908704d3a4dd6e853b completed April 20, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:43 p.m.