Triple

T8135724
Position Surface form Disambiguated ID Type / Status
Subject Elsie Marina E189964 entity
Predicate hasTitleInWork P24259 FINISHED
Object Miss Marina
Miss Marina is a fictional character, also known as Elsie Marina, who appears in a literary or dramatic work.
 E714225 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: Miss Marina | Statement: [Elsie Marina, hasTitleInWork, Miss Marina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Miss Marina
Context triple: [Elsie Marina, hasTitleInWork, Miss Marina]
  • A. Miss Bianca
    Miss Bianca is a sophisticated and brave white mouse who serves as one of the heroic rescuers in Disney’s animated adventure "The Rescuers."
  • B. Miss
    Miss is a traditional English honorific used before the surname or full name of an unmarried or younger woman.
  • C. Miss Elaina
    Miss Elaina is a playful, imaginative, and quirky young girl from the animated children's series "Daniel Tiger's Neighborhood," known for her backwards clothes and energetic personality.
  • D. Miss America
    Miss America is a World War II–era Marvel Comics superheroine, often associated with the Invaders and known for her enhanced strength, durability, and patriotic theme.
  • E. Missy
    Missy is the female incarnation of the Master, a recurring Time Lord villain and nemesis of the Doctor in the British science fiction series Doctor Who.
  • 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: Miss Marina
Triple: [Elsie Marina, hasTitleInWork, Miss Marina]
Generated description
Miss Marina is a fictional character, also known as Elsie Marina, who appears in a literary or dramatic work.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Miss Marina
Target entity description: Miss Marina is a fictional character, also known as Elsie Marina, who appears in a literary or dramatic work.
  • A. Miss Bianca
    Miss Bianca is a sophisticated and brave white mouse who serves as one of the heroic rescuers in Disney’s animated adventure "The Rescuers."
  • B. Miss
    Miss is a traditional English honorific used before the surname or full name of an unmarried or younger woman.
  • C. Miss Elaina
    Miss Elaina is a playful, imaginative, and quirky young girl from the animated children's series "Daniel Tiger's Neighborhood," known for her backwards clothes and energetic personality.
  • D. Miss America
    Miss America is a World War II–era Marvel Comics superheroine, often associated with the Invaders and known for her enhanced strength, durability, and patriotic theme.
  • E. Missy
    Missy is the female incarnation of the Master, a recurring Time Lord villain and nemesis of the Doctor in the British science fiction series Doctor Who.
  • 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_69ca82bcb4848190a9a9d036ad768642 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb43fff6e0819086c95b571272b50c completed March 31, 2026, 3:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc949065248190b67ba7aa2688903e completed April 1, 2026, 3:44 a.m.
NEDg Description generation batch_69cc95c180188190a2d541e8ea9a4c57 completed April 1, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69cc970cf55c8190abf432ac68d6bbc3 completed April 1, 2026, 3:54 a.m.
Created at: March 30, 2026, 5:35 p.m.