Triple

T1923054
Position Surface form Disambiguated ID Type / Status
Subject AlphaZero E40166 entity
Predicate defeated P4779 FINISHED
Object Elmo shogi engine
Elmo shogi engine is a highly advanced computer program for playing shogi that was strong enough to serve as a benchmark opponent for DeepMind’s AlphaZero.
 E214836 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: Elmo shogi engine | Statement: [AlphaZero, defeated, Elmo shogi engine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elmo shogi engine
Context triple: [AlphaZero, defeated, Elmo shogi engine]
  • A. Tromp
    Tromp is a Dutch surname most famously associated with the 17th-century admiral Cornelis Tromp and his naval family.
  • B. River Chess
    River Chess is a chalk stream in southeast England that flows through Buckinghamshire and Hertfordshire before joining the River Colne.
  • C. Fritz
    Fritz is an individual known primarily as the offspring of Fifi.
  • D. Zobrist
    Zobrist is a surname most notably associated with Ben Zobrist, a former Major League Baseball player and World Series MVP.
  • E. AlphaZero
    AlphaZero is a DeepMind-developed artificial intelligence system that mastered complex games like chess, shogi, and Go through self-play reinforcement learning without human-crafted strategies.
  • 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: Elmo shogi engine
Triple: [AlphaZero, defeated, Elmo shogi engine]
Generated description
Elmo shogi engine is a highly advanced computer program for playing shogi that was strong enough to serve as a benchmark opponent for DeepMind’s AlphaZero.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elmo shogi engine
Target entity description: Elmo shogi engine is a highly advanced computer program for playing shogi that was strong enough to serve as a benchmark opponent for DeepMind’s AlphaZero.
  • A. Tromp
    Tromp is a Dutch surname most famously associated with the 17th-century admiral Cornelis Tromp and his naval family.
  • B. River Chess
    River Chess is a chalk stream in southeast England that flows through Buckinghamshire and Hertfordshire before joining the River Colne.
  • C. Fritz
    Fritz is an individual known primarily as the offspring of Fifi.
  • D. Zobrist
    Zobrist is a surname most notably associated with Ben Zobrist, a former Major League Baseball player and World Series MVP.
  • E. AlphaZero
    AlphaZero is a DeepMind-developed artificial intelligence system that mastered complex games like chess, shogi, and Go through self-play reinforcement learning without human-crafted strategies.
  • 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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb23459ac819088ded5bfac9d4aad completed March 7, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3e6678881908d72de7e0f19a648 completed March 8, 2026, 10:10 p.m.
NEDg Description generation batch_69adf471909881909de20d9d1fa0b372 completed March 8, 2026, 10:13 p.m.
NED2 Entity disambiguation (via description) batch_69adf50b17a081909b93ad3e08c71772 completed March 8, 2026, 10:15 p.m.
Created at: March 4, 2026, 7:35 p.m.