Triple

T8482291
Position Surface form Disambiguated ID Type / Status
Subject Lee Sedol E200548 entity
Predicate opponent P437 FINISHED
Object AlphaGo E39541 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: AlphaGo | Statement: [Lee Sedol, opponent, AlphaGo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AlphaGo
Context triple: [Lee Sedol, opponent, AlphaGo]
  • A. AlphaGo chosen
    AlphaGo is an artificial intelligence program developed by DeepMind that became famous for defeating world champion Go players using deep neural networks and reinforcement learning.
  • B. AlphaGo Zero
    AlphaGo Zero is DeepMind's advanced artificial intelligence program that learned to play the board game Go at superhuman level entirely through self-play without human data.
  • C. 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.
  • D. AlphaStar
    AlphaStar is a DeepMind-created artificial intelligence system that achieved grandmaster-level performance in the real-time strategy game StarCraft II.
  • E. DeepMind
    DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
  • 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_69ca831b17988190a1f3f3413d57b820 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe53638c48190b742fc51d1b4442a completed March 31, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea83707e481909f9dfd6450a28d3d completed April 2, 2026, 5:32 p.m.
Created at: March 30, 2026, 6:12 p.m.