Triple

T18814762
Position Surface form Disambiguated ID Type / Status
Subject Malinska E460106 entity
Predicate knownFor P22 FINISHED
Object marina
A marina is a specially designed harbor facility that provides moorings and services for recreational boats and yachts.
 E1343791 NE FINISHED

How this triple was built (4 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: [Malinska, knownFor, marina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: marina
Context triple: [Malinska, knownFor, 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 a 2012 Tamil coming-of-age drama film that helped establish Sivakarthikeyan as a leading actor in the Tamil film industry.
  • C. Marina
    Marina is the given name of Marina von Neumann Whitman, an American economist and former General Motors executive.
  • D. Marina
    Marina is the eccentric, childlike porn actress who becomes the obsessive focus of a recently released psychiatric patient in Pedro Almodóvar’s dark romantic comedy film "Tie Me Up! Tie Me Down!".
  • E. Marina
    Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: marina
Triple: [Malinska, knownFor, marina]
Generated description
A marina is a specially designed harbor facility that provides moorings and services for recreational boats and yachts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: marina
Target entity description: A marina is a specially designed harbor facility that provides moorings and services for recreational boats and yachts.
  • 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 a 2012 Tamil coming-of-age drama film that helped establish Sivakarthikeyan as a leading actor in the Tamil film industry.
  • C. Marina
    Marina is the given name of Marina von Neumann Whitman, an American economist and former General Motors executive.
  • D. Marina
    Marina is the eccentric, childlike porn actress who becomes the obsessive focus of a recently released psychiatric patient in Pedro Almodóvar’s dark romantic comedy film "Tie Me Up! Tie Me Down!".
  • E. Marina
    Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
  • F. None of above. chosen

Provenance (5 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a3df2d3881909b336d813bbfd0aa completed April 20, 2026, 3:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a055bc7cf40819084b9b975daa86b5f completed May 14, 2026, 5:21 a.m.
NEDg Description generation batch_6a055d9a9da88190b974e8803ca8537f completed May 14, 2026, 5:28 a.m.
NED2 Entity disambiguation (via description) batch_6a055e1a22308190bb7f2337fabc5bdf completed May 14, 2026, 5:31 a.m.
Created at: April 10, 2026, 11:53 a.m.