Triple

T22033285
Position Surface form Disambiguated ID Type / Status
Subject Mrs. Gao E544137 entity
Predicate spouse P13 FINISHED
Object Mr. Gao NE NERFINISHED

How this triple was built (2 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: Mr. Gao | Statement: [Mrs. Gao, spouse, Mr. Gao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mr. Gao
Context triple: [Mrs. Gao, spouse, Mr. Gao]
  • A. Mr. Gao chosen
    Mr. Gao is the central protagonist of Ang Lee’s film "The Wedding Banquet," a Taiwanese immigrant in New York who stages a sham marriage to satisfy his traditional parents while secretly living with his male partner.
  • 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. Madame Gao
    Madame Gao is a powerful and enigmatic crime boss in the Marvel Netflix series, known for her deep connections to the Hand and her influence over New York’s criminal underworld.
  • D. Señor Chang
    Señor Chang is the unhinged, often antagonistic Spanish teacher-turned-student from the TV series "Community," known for his erratic behavior and over-the-top antics.
  • E. Gao Huang
    Gao Huang is a computer scientist and researcher in deep learning, best known for co-developing the DenseNet convolutional neural network architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e2f98c8819083e11eab90942a78 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127ef97348190b8dcdcad11694ebe completed April 28, 2026, 9:34 p.m.
Created at: April 16, 2026, 8:24 p.m.