Triple

T7470940
Position Surface form Disambiguated ID Type / Status
Subject Marina Nikolayevna Prusakova E176501 entity
Predicate givenName P17 FINISHED
Object Marina E270577 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: Marina | Statement: [Marina Nikolayevna Prusakova, givenName, Marina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marina
Context triple: [Marina Nikolayevna Prusakova, givenName, Marina]
  • A. Marina
    Marina is a recurring comedic character in the long-running British sitcom "Last of the Summer Wine," known for her flirtatious relationship with the married Howard.
  • B. Marina
    Marina is the given name of Marina von Neumann Whitman, an American economist and former General Motors executive.
  • C. Marina chosen
    Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
  • D. Lissa
    Lissa is a historic town in western Poland, known today as Leszno, that was once part of Germany and is notable as the birthplace of several prominent Jewish and intellectual figures.
  • E. Kamarina
    Kamarina is a modern settlement in the Epirus region of northwestern Greece, located near the archaeological site of ancient Cassope.
  • 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_69c69f223fd88190b4c69b95d7cbeeda completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f4145d608190bd93239f04f7da41 completed March 27, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8347b36388190989d2bcbe3f747bf completed March 28, 2026, 8:05 p.m.
Created at: March 27, 2026, 3:41 p.m.