Triple

T18338925
Position Surface form Disambiguated ID Type / Status
Subject Jen Taylor E439347 entity
Predicate voiceRole P12691 FINISHED
Object Lina
Lina is a fictional character voiced by American actress Jen Taylor, known for her work in video games and animation.
 E1318170 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: Lina | Statement: [Jen Taylor, voiceRole, Lina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lina
Context triple: [Jen Taylor, voiceRole, Lina]
  • A. Lina
    Lina is a Native American servant in Toni Morrison’s novel *A Mercy*, whose history of displacement and resilience reflects the novel’s themes of slavery, colonialism, and survival in 17th-century America.
  • B. Lina
    Lina Heydrich was the wife of high-ranking Nazi official Reinhard Heydrich and a committed supporter of National Socialism in Germany.
  • C. Lina
    Lina is a female lion character who serves as one of the official mascots for the Japanese professional baseball team Saitama Seibu Lions.
  • D. Lina
    Lina is a feminine given name used in various cultures, often as a short form of names like Angelina, Karolina, or Alina.
  • E. Lina
    Lina is one of the four main playable characters in the Japanese video game *Yume Kōjō: Doki Doki Panic*, which later served as the basis for *Super Mario Bros. 2* in the West.
  • 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: Lina
Triple: [Jen Taylor, voiceRole, Lina]
Generated description
Lina is a fictional character voiced by American actress Jen Taylor, known for her work in video games and animation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lina
Target entity description: Lina is a fictional character voiced by American actress Jen Taylor, known for her work in video games and animation.
  • A. Lina
    Lina is a Native American servant in Toni Morrison’s novel *A Mercy*, whose history of displacement and resilience reflects the novel’s themes of slavery, colonialism, and survival in 17th-century America.
  • B. Lina
    Lina Heydrich was the wife of high-ranking Nazi official Reinhard Heydrich and a committed supporter of National Socialism in Germany.
  • C. Lina
    Lina is a female lion character who serves as one of the official mascots for the Japanese professional baseball team Saitama Seibu Lions.
  • D. Lina
    Lina is a feminine given name used in various cultures, often as a short form of names like Angelina, Karolina, or Alina.
  • E. Lina
    Lina is one of the four main playable characters in the Japanese video game *Yume Kōjō: Doki Doki Panic*, which later served as the basis for *Super Mario Bros. 2* in the West.
  • 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_69d8b9175fec8190af865699b4e64d8c completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50ed07db48190a15e957c96b1c5bf completed April 19, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03c4d4bcb08190ae701be702c0c743 completed May 13, 2026, 12:24 a.m.
NEDg Description generation batch_6a03c592f7d0819082d600901da2c2f6 completed May 13, 2026, 12:28 a.m.
NED2 Entity disambiguation (via description) batch_6a03c63ec8c48190bad47d423ab2cfe7 completed May 13, 2026, 12:30 a.m.
Created at: April 10, 2026, 10:37 a.m.