Triple

T20112319
Position Surface form Disambiguated ID Type / Status
Subject Esteemsters E490363 entity
Predicate introducesCharacter P12208 FINISHED
Object Ms. Li
Ms. Li is a strict, deadpan high school teacher character from the animated TV series "Daria."
 E1411796 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: Ms. Li | Statement: [Esteemsters, introducesCharacter, Ms. Li]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ms. Li
Context triple: [Esteemsters, introducesCharacter, Ms. Li]
  • A. Ms. Li
    Ms. Li is a character from the animated television series "Daria," known as the strict and image-conscious principal of Lawndale High School.
  • B. Mrs. Gao
    Mrs. Gao is a traditional, strong-willed Taiwanese mother whose expectations and cultural values drive much of the emotional conflict in Ang Lee’s film "The Wedding Banquet."
  • C. Ms. Toi
    Ms. Toi is an American rapper best known for her featured verse on Ice Cube’s hit single “You Can Do It.”
  • D. Ms. Weiss
    Ms. Weiss is a social worker character in the film "Precious," known for her pivotal role in supporting the abused teenage protagonist.
  • E. Madame Peng
    Madame Peng is the honorific name commonly used for Peng Liyuan, a renowned Chinese soprano and the wife of Chinese leader Xi Jinping.
  • 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: Ms. Li
Triple: [Esteemsters, introducesCharacter, Ms. Li]
Generated description
Ms. Li is a strict, deadpan high school teacher character from the animated TV series "Daria."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ms. Li
Target entity description: Ms. Li is a strict, deadpan high school teacher character from the animated TV series "Daria."
  • A. Ms. Li chosen
    Ms. Li is a character from the animated television series "Daria," known as the strict and image-conscious principal of Lawndale High School.
  • B. Mrs. Gao
    Mrs. Gao is a traditional, strong-willed Taiwanese mother whose expectations and cultural values drive much of the emotional conflict in Ang Lee’s film "The Wedding Banquet."
  • C. Ms. Toi
    Ms. Toi is an American rapper best known for her featured verse on Ice Cube’s hit single “You Can Do It.”
  • D. Ms. Weiss
    Ms. Weiss is a social worker character in the film "Precious," known for her pivotal role in supporting the abused teenage protagonist.
  • E. Madame Peng
    Madame Peng is the honorific name commonly used for Peng Liyuan, a renowned Chinese soprano and the wife of Chinese leader Xi Jinping.
  • F. None of above.

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_69da62636cc08190982cc71733a17b8d completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e666e21f908190b46c747662ff378a completed April 20, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a083464ab0881909e0395771491499d completed May 16, 2026, 9:09 a.m.
NEDg Description generation batch_6a08366132148190a316f28e027664eb completed May 16, 2026, 9:18 a.m.
NED2 Entity disambiguation (via description) batch_6a08370f25c4819085da226ded7ae658 completed May 16, 2026, 9:21 a.m.
Created at: April 11, 2026, 11:29 p.m.