Triple

T2330640
Position Surface form Disambiguated ID Type / Status
Subject Turning Red E48392 entity
Predicate mainCharacter P1183 FINISHED
Object Miriam Mendelsohn
Miriam Mendelsohn is a loyal, upbeat, and supportive best friend of Mei Lee in Pixar's animated film "Turning Red."
E316906 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: Miriam Mendelsohn | Statement: [Turning Red, mainCharacter, Miriam Mendelsohn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miriam Mendelsohn
Context triple: [Turning Red, mainCharacter, Miriam Mendelsohn]
  • A. Miriam Bienstock
    Miriam Bienstock was an American music industry executive and co-founder of Atlantic Records who played a key role in shaping the label’s early business operations and success.
  • B. Helene Shapiro
    Helene Shapiro is an American mathematician known for her work in linear algebra and matrix theory, and as a student of Olga Taussky-Todd.
  • C. Esther Raab
    Esther Raab was a Jewish Holocaust survivor known for escaping from the Sobibor extermination camp and later bearing witness to its atrocities.
  • D. Leila Gerstein
    Leila Gerstein is an American television writer and producer best known for creating the comedy-drama series "Hart of Dixie."
  • E. Maria Nuzberg
    Maria Nuzberg was the wife of Vasily Stalin, the son of Soviet leader Joseph Stalin.
  • 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: Miriam Mendelsohn
Triple: [Turning Red, mainCharacter, Miriam Mendelsohn]
Generated description
Miriam Mendelsohn is a loyal, upbeat, and supportive best friend of Mei Lee in Pixar's animated film "Turning Red."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Miriam Mendelsohn
Target entity description: Miriam Mendelsohn is a loyal, upbeat, and supportive best friend of Mei Lee in Pixar's animated film "Turning Red."
  • A. Miriam Bienstock
    Miriam Bienstock was an American music industry executive and co-founder of Atlantic Records who played a key role in shaping the label’s early business operations and success.
  • B. Helene Shapiro
    Helene Shapiro is an American mathematician known for her work in linear algebra and matrix theory, and as a student of Olga Taussky-Todd.
  • C. Esther Raab
    Esther Raab was a Jewish Holocaust survivor known for escaping from the Sobibor extermination camp and later bearing witness to its atrocities.
  • D. Leila Gerstein
    Leila Gerstein is an American television writer and producer best known for creating the comedy-drama series "Hart of Dixie."
  • E. Maria Nuzberg
    Maria Nuzberg was the wife of Vasily Stalin, the son of Soviet leader Joseph Stalin.
  • 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc669956881908b8d9784d6a06acf completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108bbc090819092b76eb134aad909 completed March 11, 2026, 6:16 a.m.
NEDg Description generation batch_69b10b6cead481908ad8ff7e65caebcf completed March 11, 2026, 6:27 a.m.
NED2 Entity disambiguation (via description) batch_69b10f1ed9e88190ae4b06611d0c772c completed March 11, 2026, 6:43 a.m.
Created at: March 4, 2026, 7:50 p.m.