Triple

T9892907
Position Surface form Disambiguated ID Type / Status
Subject ByteDance E181496 entity
Predicate coFounder P2835 FINISHED
Object Liang Rubo E828489 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: Liang Rubo | Statement: [ByteDance, coFounder, Liang Rubo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liang Rubo
Context triple: [ByteDance, coFounder, Liang Rubo]
  • A. Liang Rubo chosen
    Liang Rubo is a Chinese entrepreneur best known as a co-founder and current CEO of ByteDance, the tech company behind TikTok and Douyin.
  • B. Liang Wengen
    Liang Wengen is a Chinese billionaire entrepreneur best known as the founder and chairman of Sany Group, one of the world’s leading heavy machinery manufacturers.
  • C. Liu Bin
    Liu Bin is a Chinese woman known primarily as the wife of Mao Xinyu, the grandson of Mao Zedong.
  • D. Li Rusong
    Li Rusong was a Ming dynasty general renowned for leading Chinese forces to aid Korea against Toyotomi Hideyoshi’s invasions in the late 16th century.
  • E. Liu Dong
    Liu Dong is a Chinese middle-distance runner best known for winning the women's 1500 metres world title in 1993 as part of coach Ma Junren's famed "Ma's Army."
  • 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_69ca8283a6708190801af7a25a7ebb9f completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb4814a3c8190ab1fd7f755a44508 completed April 2, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20d888b408190a68ff55d63558478 completed April 5, 2026, 7:21 a.m.
Created at: March 30, 2026, 8:39 p.m.