Triple

T408124
Position Surface form Disambiguated ID Type / Status
Subject Konrad Adenauer E9425 entity
Predicate residence P75 FINISHED
Object Cologne E35950 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: Cologne | Statement: [Konrad Adenauer, residence, Cologne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cologne
Context triple: [Konrad Adenauer, residence, Cologne]
  • A. Cologne chosen
    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.
  • B. 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.
  • C. Mannheim
    Mannheim is a major city in southwestern Germany, known as an important industrial, commercial, and cultural center at the confluence of the Rhine and Neckar rivers.
  • D. Duisburg
    Duisburg is a major industrial and port city in western Germany’s Ruhr region, known for its steel production and one of the world’s largest inland harbors.
  • E. Bonn
    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.
  • 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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ecbf0650819080753815ca280eec completed Feb. 28, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69acddeda4f8819080d37aea0fd4b092 completed March 8, 2026, 2:24 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.