Triple

T11874351
Position Surface form Disambiguated ID Type / Status
Subject European law enforcement agencies E282486 entity
Predicate cooperateWith 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: [European law enforcement agencies, cooperateWith, Europol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Europol
Context triple: [European law enforcement agencies, cooperateWith, 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8be1a22448190bd0722188c14d7bd completed April 10, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f281cac9a48190b4b0f4c53b41110f completed April 29, 2026, 10:10 p.m.
Created at: April 8, 2026, 9:44 p.m.