Triple

T9130443
Position Surface form Disambiguated ID Type / Status
Subject Mohamed Atta E219071 entity
Predicate residence P75 FINISHED
Object Hamburg E7419 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: Hamburg | Statement: [Mohamed Atta, residence, Hamburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamburg
Context triple: [Mohamed Atta, residence, Hamburg]
  • A. Hamburg chosen
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • B. Bremen
    Bremen is a city-state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port on the Weser River.
  • C. Gotenhafen
    Gotenhafen was the German name for the port city of Gdynia in occupied Poland during World War II, used as a major naval base by the Kriegsmarine.
  • D. Hamburg and Lübeck
    Hamburg and Lübeck is a diocese of the Evangelical Lutheran Church in Northern Germany that encompasses the historic Hanseatic cities of Hamburg and Lübeck and their surrounding regions.
  • E. Lübeck
    Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
  • 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_69ca83debfc0819095800583e97ab10f completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8cdafb48190be5e62b15779d771 completed April 1, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05436de048190a884b7158f9281f7 completed April 3, 2026, 11:58 p.m.
Created at: March 30, 2026, 7:18 p.m.