Triple

T2654689
Position Surface form Disambiguated ID Type / Status
Subject Princess Marina of Greece and Denmark E53980 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: [Princess Marina of Greece and Denmark, givenName, Marina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marina
Context triple: [Princess Marina of Greece and Denmark, 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 chosen
    Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
  • C. Marina
    Marina is the given name of Marina von Neumann Whitman, an American economist and former General Motors executive.
  • 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. Theodosia
    Theodosia is a historic port city on the southeastern coast of Crimea, known for its long history as a trading center on the Black Sea.
  • 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_69ab495e192081909c77b622e8e7e15a completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd932a35881909568839589f12062 completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98d0dbd08190a317dfe1844840c5 completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:53 p.m.