Triple

T20277435
Position Surface form Disambiguated ID Type / Status
Subject Grand Ducal Police E503051 entity
Predicate cooperatesWith P435 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: [Grand Ducal Police, cooperatesWith, Europol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Europol
Context triple: [Grand Ducal Police, cooperatesWith, 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. Evra
    Evra is a French former professional footballer best known for his successful career as a left-back with Manchester United and the French national team.
  • C. Europaeum
    Europaeum is a network of leading European universities dedicated to promoting academic collaboration, European studies, and cross-border dialogue in higher education.
  • D. Europos
    Europos was an ancient Macedonian town traditionally identified as the birthplace of the Seleucid Empire’s founder, Seleucus I Nicator.
  • E. Europos
    Europos is an ancient city historically known as Rayy (or Rey), located near modern-day Tehran in Iran and recognized as one of the oldest continuously inhabited settlements in the region.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675e4cdfc81908c7cb4519a7d744b completed April 20, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a085a23a5f88190958b045de0b64087 completed May 16, 2026, 11:50 a.m.
Created at: April 16, 2026, 10:35 a.m.