Triple

T3084230
Position Surface form Disambiguated ID Type / Status
Subject The Marvelous Mrs. Maisel E64330 entity
Predicate character P662 FINISHED
Object Mei Lin
Mei Lin is a sharp, ambitious Chinese-American medical student and love interest of Joel Maisel in the television series "The Marvelous Mrs. Maisel."
 E325146 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: Mei Lin | Statement: [The Marvelous Mrs. Maisel, character, Mei Lin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mei Lin
Context triple: [The Marvelous Mrs. Maisel, character, Mei Lin]
  • A. Mei-ling
    Mei-ling is the given name of Soong Mei-ling, the influential 20th-century Chinese political figure and wife of Chiang Kai-shek.
  • B. Htee Khee
    Htee Khee is a border town in Myanmar that serves as a key crossing and trade gateway with neighboring Thailand.
  • C. Meilin "Mei" Lee
    Meilin "Mei" Lee is the energetic 13-year-old Chinese-Canadian girl in Pixar's "Turning Red" who transforms into a giant red panda whenever her emotions become overwhelming.
  • D. Nai Leng
    Nai Leng is an actor known for his role in the film "Chang: A Drama of the Wilderness."
  • E. Tan Hooi Ling
    Tan Hooi Ling is a Malaysian entrepreneur best known as the co-founder of Grab, Southeast Asia’s leading super-app for ride-hailing, deliveries, and digital financial services.
  • 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: Mei Lin
Triple: [The Marvelous Mrs. Maisel, character, Mei Lin]
Generated description
Mei Lin is a sharp, ambitious Chinese-American medical student and love interest of Joel Maisel in the television series "The Marvelous Mrs. Maisel."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mei Lin
Target entity description: Mei Lin is a sharp, ambitious Chinese-American medical student and love interest of Joel Maisel in the television series "The Marvelous Mrs. Maisel."
  • A. Mei-ling
    Mei-ling is the given name of Soong Mei-ling, the influential 20th-century Chinese political figure and wife of Chiang Kai-shek.
  • B. Htee Khee
    Htee Khee is a border town in Myanmar that serves as a key crossing and trade gateway with neighboring Thailand.
  • C. Meilin "Mei" Lee
    Meilin "Mei" Lee is the energetic 13-year-old Chinese-Canadian girl in Pixar's "Turning Red" who transforms into a giant red panda whenever her emotions become overwhelming.
  • D. Nai Leng
    Nai Leng is an actor known for his role in the film "Chang: A Drama of the Wilderness."
  • E. Tan Hooi Ling
    Tan Hooi Ling is a Malaysian entrepreneur best known as the co-founder of Grab, Southeast Asia’s leading super-app for ride-hailing, deliveries, and digital financial services.
  • 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_69ad857bb4c88190a4cf27893fcabed8 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada1e98a1c8190b1dd4a0a47f7d6c6 completed March 8, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f89b650c8190983a00e37a42a794 completed March 11, 2026, 11:19 p.m.
NEDg Description generation batch_69b1f992a8ec8190b3e37dddd93ac57b completed March 11, 2026, 11:24 p.m.
NED2 Entity disambiguation (via description) batch_69b1f9f759408190a4f2121078fe13cb completed March 11, 2026, 11:25 p.m.
Created at: March 8, 2026, 3:03 p.m.