Triple

T10931905
Position Surface form Disambiguated ID Type / Status
Subject Claudiu Bumba E258226 entity
Predicate leagueParticipatedIn P2209 FINISHED
Object Nemzeti Bajnokság I E815373 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: Nemzeti Bajnokság I | Statement: [Claudiu Bumba, leagueParticipatedIn, Nemzeti Bajnokság I]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nemzeti Bajnokság I
Context triple: [Claudiu Bumba, leagueParticipatedIn, Nemzeti Bajnokság I]
  • A. Nemzeti Bajnokság I chosen
    Nemzeti Bajnokság I is the top professional football league in Hungary, featuring the country’s leading clubs in its premier domestic competition.
  • B. Liga Națională
    Liga Națională is Romania’s top-tier professional basketball league, featuring the country’s leading clubs in national competition.
  • C. Milli Lig
    Milli Lig was the original name of Turkey’s top professional football league, which later became known as the Süper Lig.
  • D. Magyar Kupa
    Magyar Kupa is Hungary’s premier national football cup competition, contested annually by clubs from across the country.
  • E. Erovnuli Liga
    Erovnuli Liga is the top professional football division in Georgia, featuring the country’s leading clubs in its premier league competition.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770a062f481908beb76c6dbaeb6a6 completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2176328448190bbce6735ec97507a completed April 17, 2026, 11:20 a.m.
Created at: April 8, 2026, 9:23 p.m.