Triple

T15793986
Position Surface form Disambiguated ID Type / Status
Subject Deep Thought E382928 entity
Predicate developer P73 FINISHED
Object Feng-hsiung Hsu E1177637 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: Feng-hsiung Hsu | Statement: [Deep Thought, developer, Feng-hsiung Hsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Feng-hsiung Hsu
Context triple: [Deep Thought, developer, Feng-hsiung Hsu]
  • A. Feng-hsiung Hsu chosen
    Feng-hsiung Hsu is a computer scientist and engineer best known for leading the development of IBM’s Deep Blue, the first chess computer to defeat a reigning world champion.
  • B. Arthur Samuel Allen
    Arthur Samuel Allen was an Australian Army major general who led key campaigns in the Middle East and Pacific during the Second World War.
  • C. Nils Nilsson
    Nils Nilsson was a pioneering American computer scientist and AI researcher known for foundational work in search algorithms, robotics, and the early development of artificial intelligence as an academic field.
  • D. Michael L. Littman
    Michael L. Littman is an American computer scientist and professor known for his influential research in reinforcement learning, machine learning, and artificial intelligence.
  • E. Arthur Guez
    Arthur Guez is a machine learning researcher known for his contributions to deep reinforcement learning, including co-developing the Double DQN algorithm.
  • 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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4db55308190875a04f982c44cea completed April 16, 2026, 10:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff998981088190b9ce9d99c0481e21 completed May 9, 2026, 8:31 p.m.
Created at: April 10, 2026, 4:48 a.m.