Triple

T2407508
Position Surface form Disambiguated ID Type / Status
Subject Directorate-General for Migration and Home Affairs E50309 entity
Predicate overseesAgency P760 FINISHED
Object Europol E36588 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: Europol | Statement: [Directorate-General for Migration and Home Affairs, overseesAgency, Europol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Europol
Context triple: [Directorate-General for Migration and Home Affairs, overseesAgency, Europol]
  • A. Europol chosen
    Europol is the European Union’s law enforcement agency that supports member states in combating serious international crime and terrorism.
  • B. Europaeum
    Europaeum is a network of leading European universities dedicated to promoting academic collaboration, European studies, and cross-border dialogue in higher education.
  • C. Belonia
    Belonia is a small town in the South Tripura district of the Indian state of Tripura, near the India–Bangladesh border.
  • D. Hollandia
    Hollandia is an engineering firm known for its role in designing and constructing major structures such as the London Eye.
  • E. Nordavia
    Nordavia was a Russian regional airline that rebranded as Smartavia, operating domestic and some international routes primarily from northern Russia.
  • 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_69a88b0339a88190a1207333cd271cc9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc8fcd3008190b27325e6829ae7ce completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3eba9d08190a2c63e590e08b4df completed March 9, 2026, 11:50 a.m.
Created at: March 4, 2026, 7:58 p.m.