Triple

T20593948
Position Surface form Disambiguated ID Type / Status
Subject Béla Ferenc Dezső Blaskó E506001 entity
Predicate birthPlace P1 FINISHED
Object Lugos 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: Lugos | Statement: [Béla Ferenc Dezső Blaskó, birthPlace, Lugos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lugos
Context triple: [Béla Ferenc Dezső Blaskó, birthPlace, Lugos]
  • A. Lugos chosen
    Lugos is a town in present-day Romania, historically part of the Austro-Hungarian Empire, known as the birthplace of actor Bela Lugosi.
  • B. Luga
    Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
  • C. Lübars
    Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
  • D. Lebedos
    Lebedos was an ancient Ionian Greek city on the western coast of Asia Minor, known as one of the twelve cities of the Ionian League.
  • E. Lugo
    Lugo is a historic city in northwestern Spain known for its remarkably well-preserved Roman walls, a UNESCO World Heritage Site.
  • 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_69e0b4ba6ae88190af871e1f9522c704 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a97e3a7c8190b0b4604aaf40564b completed April 20, 2026, 10:32 p.m.
Created at: April 16, 2026, 11:40 a.m.