Triple

T8802526
Position Surface form Disambiguated ID Type / Status
Subject Sivakarthikeyan E209445 entity
Predicate notableWork P4 FINISHED
Object Marina
Marina is a 2012 Tamil coming-of-age drama film that helped establish Sivakarthikeyan as a leading actor in the Tamil film industry.
 E759162 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: [Sivakarthikeyan, notableWork, Marina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marina
Context triple: [Sivakarthikeyan, notableWork, 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
    Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
  • D. Marina Severa
    Marina Severa was a Roman empress of the 4th century, known as the first wife of Emperor Valentinian I and the mother of Emperor Gratian.
  • E. 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.
  • 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: [Sivakarthikeyan, notableWork, Marina]
Generated description
Marina is a 2012 Tamil coming-of-age drama film that helped establish Sivakarthikeyan as a leading actor in the Tamil film industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marina
Target entity description: Marina is a 2012 Tamil coming-of-age drama film that helped establish Sivakarthikeyan as a leading actor in the Tamil film industry.
  • 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
    Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
  • D. Marina Severa
    Marina Severa was a Roman empress of the 4th century, known as the first wife of Emperor Valentinian I and the mother of Emperor Gratian.
  • E. 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.
  • 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_69ca836320e48190b5cf585b90a322c4 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fbb5b108190a9f889d40aa20521 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f799f00819089159da177c816e9 completed April 3, 2026, 7:42 a.m.
NEDg Description generation batch_69cf708dbd54819099efa4b5729d6298 completed April 3, 2026, 7:47 a.m.
NED2 Entity disambiguation (via description) batch_69cf7163e2088190bf252896cc4036b2 completed April 3, 2026, 7:51 a.m.
Created at: March 30, 2026, 6:44 p.m.