Triple

T7198746
Position Surface form Disambiguated ID Type / Status
Subject Marina Oswald E168682 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 Oswald, givenName, Marina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marina
Context triple: [Marina Oswald, 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_69c68a5376748190bb500f03df86e93e completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6e92b8bc08190bfcdd34ce42e3448 completed March 27, 2026, 8:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bfac10c88190ad83da6a137abd27 completed March 28, 2026, 11:46 a.m.
Created at: March 27, 2026, 2:52 p.m.