Triple

T18518991
Position Surface form Disambiguated ID Type / Status
Subject Maria Lilina E452536 entity
Predicate familyName P18 FINISHED
Object Lilina
Lilina is a Japanese surname most notably borne by Maria Lilina, a historical figure associated with this family name.
 E1329142 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: Lilina | Statement: [Maria Lilina, familyName, Lilina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lilina
Context triple: [Maria Lilina, familyName, Lilina]
  • A. Lilia
    Lilia is a feminine given name, often considered a variant of Lily and associated with the elegance and symbolism of the lily flower.
  • B. 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.
  • C. 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.
  • D. Lina
    Lina is a fictional character voiced by American actress Jen Taylor, known for her work in video games and animation.
  • E. Lina
    Lina Heydrich was the wife of high-ranking Nazi official Reinhard Heydrich and a committed supporter of National Socialism in Germany.
  • 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: Lilina
Triple: [Maria Lilina, familyName, Lilina]
Generated description
Lilina is a Japanese surname most notably borne by Maria Lilina, a historical figure associated with this family name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lilina
Target entity description: Lilina is a Japanese surname most notably borne by Maria Lilina, a historical figure associated with this family name.
  • A. Lilia
    Lilia is a feminine given name, often considered a variant of Lily and associated with the elegance and symbolism of the lily flower.
  • B. 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.
  • C. 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.
  • D. Lina
    Lina is a fictional character voiced by American actress Jen Taylor, known for her work in video games and animation.
  • E. Lina
    Lina Heydrich was the wife of high-ranking Nazi official Reinhard Heydrich and a committed supporter of National Socialism in Germany.
  • 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_69d8d386df84819092355ebb260d848e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5338ce7e481908ee69ffe4f30d5a4 completed April 19, 2026, 7:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a04916eeed88190bf8df75fc83ba145 completed May 13, 2026, 2:57 p.m.
NEDg Description generation batch_6a04924c2fd08190a824c470b732626f completed May 13, 2026, 3:01 p.m.
NED2 Entity disambiguation (via description) batch_6a0492e3a6dc8190902bb46bec64c07e completed May 13, 2026, 3:04 p.m.
Created at: April 10, 2026, 11:36 a.m.