Triple

T1497808
Position Surface form Disambiguated ID Type / Status
Subject Maximilian de Angelis E29725 entity
Predicate placeOfBirth P1 FINISHED
Object Budapest E13406 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: Budapest | Statement: [Maximilian de Angelis, placeOfBirth, Budapest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Budapest
Context triple: [Maximilian de Angelis, placeOfBirth, Budapest]
  • A. Budapest chosen
    Budapest is the capital and largest city of Hungary, renowned for its historic architecture, thermal baths, and prominent location along the Danube River.
  • B. Siófok
    Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
  • C. Pozsony
    Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
  • D. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • E. Pécs
    Pécs is a historic cultural and university city in southwestern Hungary, renowned for its Roman and Ottoman heritage and its designation as a European Capital of Culture in 2010.
  • 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6ef5ce88190a6b520525a6d42a3 completed March 1, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae891d41d88190aec6987c64c99757 completed March 9, 2026, 8:47 a.m.
Created at: March 1, 2026, 8:12 p.m.