Triple

T1471463
Position Surface form Disambiguated ID Type / Status
Subject Federal Ministry of Education and Research E27143 entity
Predicate headquartersLocation P62 FINISHED
Object Bonn E23133 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: Bonn | Statement: [Federal Ministry of Education and Research, headquartersLocation, Bonn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bonn
Context triple: [Federal Ministry of Education and Research, headquartersLocation, Bonn]
  • A. Bonn chosen
    Bonn is a historic German city on the Rhine River, best known for being the birthplace of Ludwig van Beethoven and the former seat of the federal government before reunification.
  • B. Cologne
    Cologne is a historic German city on the Rhine River, renowned for its Gothic cathedral, vibrant cultural scene, and status as a major economic and media hub.
  • C. Düsseldorf
    Düsseldorf is a major German city on the Rhine River known for its fashion and art scenes, modern architecture, and status as an important economic and financial center.
  • D. Wiesbaden
    Wiesbaden is a historic spa city in western Germany known for its thermal springs, elegant architecture, and role as a regional administrative and cultural center.
  • E. Koblenz
    Koblenz is a historic German city in Rhineland-Palatinate, known for its strategic location at the confluence of the Rhine and Moselle rivers and its well-preserved fortresses and old town.
  • 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_69a496d25d6881909dbd84f86d763992 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c5db55948190ae5262a70a161b87 completed March 1, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38b9e52688190bd9dc7fb17e892f8 completed March 13, 2026, 3:59 a.m.
Created at: March 1, 2026, 8:01 p.m.