Triple

T17124617
Position Surface form Disambiguated ID Type / Status
Subject Third Field Army E415559 entity
Predicate hadPoliticalCommissar P110057 FINISHED
Object Rao Shushi
Rao Shushi was a senior Chinese Communist Party leader and revolutionary who held key political and military posts in the early People’s Republic of China before later being purged.
E1251277 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: Rao Shushi | Statement: [Third Field Army, hadPoliticalCommissar, Rao Shushi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rao Shushi
Context triple: [Third Field Army, hadPoliticalCommissar, Rao Shushi]
  • A. Shōkū
    Shōkū was a prominent Japanese Buddhist monk of the Kamakura period and a leading disciple of Hōnen who helped develop and spread Pure Land (Jōdo) teachings.
  • B. Donaka Mark
    Donaka Mark is the main villain in the martial arts film "Man of Tai Chi," a ruthless underground fight promoter portrayed by Keanu Reeves.
  • C. Sadaharu
    Sadaharu is the given name of Sadaharu Oh, the legendary Japanese-Taiwanese baseball player and home run record holder.
  • D. Nobu
    Nobu is a common Japanese given name and name element that can appear in various masculine and unisex names.
  • E. Koji Sato
    Koji Sato is a Japanese automotive executive who serves as the president and CEO of Toyota Motor Corporation.
  • 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: Rao Shushi
Triple: [Third Field Army, hadPoliticalCommissar, Rao Shushi]
Generated description
Rao Shushi was a senior Chinese Communist Party leader and revolutionary who held key political and military posts in the early People’s Republic of China before later being purged.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rao Shushi
Target entity description: Rao Shushi was a senior Chinese Communist Party leader and revolutionary who held key political and military posts in the early People’s Republic of China before later being purged.
  • A. Shōkū
    Shōkū was a prominent Japanese Buddhist monk of the Kamakura period and a leading disciple of Hōnen who helped develop and spread Pure Land (Jōdo) teachings.
  • B. Donaka Mark
    Donaka Mark is the main villain in the martial arts film "Man of Tai Chi," a ruthless underground fight promoter portrayed by Keanu Reeves.
  • C. Sadaharu
    Sadaharu is the given name of Sadaharu Oh, the legendary Japanese-Taiwanese baseball player and home run record holder.
  • D. Nobu
    Nobu is a common Japanese given name and name element that can appear in various masculine and unisex names.
  • E. Koji Sato
    Koji Sato is a Japanese automotive executive who serves as the president and CEO of Toyota Motor Corporation.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f025fce481908e261f2e363e14f9 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a12a7288190911c1be2667916c0 completed May 11, 2026, 2:08 a.m.
NEDg Description generation batch_6a013a8e69388190b8d48d70a28e99bd completed May 11, 2026, 2:10 a.m.
NED2 Entity disambiguation (via description) batch_6a013b6824888190853cf36548507e1b completed May 11, 2026, 2:14 a.m.
Created at: April 10, 2026, 5:36 a.m.