Triple

T8335398
Position Surface form Disambiguated ID Type / Status
Subject Annabelle E195774 entity
Predicate mainCharacter P1183 FINISHED
Object Mia Form
Mia Form is the central protagonist of the story featuring Annabelle, around whom the main plot and character development revolve.
 E724828 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: Mia Form | Statement: [Annabelle, mainCharacter, Mia Form]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mia Form
Context triple: [Annabelle, mainCharacter, Mia Form]
  • A. Mia X
    Mia X is an American rapper from New Orleans known as one of the prominent female artists of Master P’s No Limit Records in the 1990s.
  • B. Mia
    Mia is a major fine art museum in Minneapolis, Minnesota, known for its extensive and diverse collection spanning thousands of years and cultures.
  • C. Mia
    Mia is a feminine given name used in many cultures, often as a short form of names like Maria or Amelia.
  • D. Mia Michaels
    Mia Michaels is an Emmy-winning American choreographer renowned for her emotionally powerful contemporary dance works on stage, television, and film.
  • E. Mia Sara
    Mia Sara is an American actress best known for her role as Sloane Peterson in the 1986 teen comedy film "Ferris Bueller's Day Off."
  • 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: Mia Form
Triple: [Annabelle, mainCharacter, Mia Form]
Generated description
Mia Form is the central protagonist of the story featuring Annabelle, around whom the main plot and character development revolve.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mia Form
Target entity description: Mia Form is the central protagonist of the story featuring Annabelle, around whom the main plot and character development revolve.
  • A. Mia X
    Mia X is an American rapper from New Orleans known as one of the prominent female artists of Master P’s No Limit Records in the 1990s.
  • B. Mia
    Mia is a feminine given name used in many cultures, often as a short form of names like Maria or Amelia.
  • C. Mia
    Mia is a major fine art museum in Minneapolis, Minnesota, known for its extensive and diverse collection spanning thousands of years and cultures.
  • D. Mia Michaels
    Mia Michaels is an Emmy-winning American choreographer renowned for her emotionally powerful contemporary dance works on stage, television, and film.
  • E. Mia Sara
    Mia Sara is an American actress best known for her role as Sloane Peterson in the 1986 teen comedy film "Ferris Bueller's Day Off."
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fd2ca648190991e398ba70caf8d completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95d9b92c8190b1eb0e64aa7ea59e completed April 1, 2026, 10:02 p.m.
NEDg Description generation batch_69cda342c10881908ebafc7853815424 completed April 1, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_69cdab736f208190a90bd4344b21a22c completed April 1, 2026, 11:34 p.m.
Created at: March 30, 2026, 5:57 p.m.