Triple

T3156428
Position Surface form Disambiguated ID Type / Status
Subject Wendi Deng E65995 entity
Predicate name P16 FINISHED
Object Wendi Deng E65995 NE FINISHED

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: Wendi Deng | Statement: [Wendi Deng, name, Wendi Deng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wendi Deng
Context triple: [Wendi Deng, name, Wendi Deng]
  • A. Wendi Deng chosen
    Wendi Deng is a Chinese-American businesswoman and film producer best known for her high-profile marriage to media mogul Rupert Murdoch and her influential connections in global media and politics.
  • B. Ding Ling
    Ding Ling was a prominent 20th-century Chinese writer and feminist known for her revolutionary literature and involvement in leftist and Communist cultural movements.
  • C. Lori Huang
    Lori Huang is the wife of NVIDIA co-founder and CEO Jensen Huang and is known for her low public profile despite her connection to the prominent tech executive.
  • D. Vivian Chan
    Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
  • E. Cathy Zhang
    Cathy Zhang is a Chinese entrepreneur best known as a founder of the multinational technology conglomerate Alibaba Group.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85850c1481908a9e9c6242238de2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5eafa4c8190a65cc1312823144c completed March 8, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b225068444819080e2b8b6b1260613 completed March 12, 2026, 2:29 a.m.
Created at: March 8, 2026, 3:05 p.m.