Triple

T16587316
Position Surface form Disambiguated ID Type / Status
Subject Brandon Walsh E402991 entity
Predicate friend P8712 FINISHED
Object David Silver E399307 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: David Silver | Statement: [Brandon Walsh, friend, David Silver]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Silver
Context triple: [Brandon Walsh, friend, David Silver]
  • A. David Silver chosen
    David Silver is a central character on the teen drama series "Beverly Hills, 90210," known for his evolution from an awkward outsider to a popular DJ and radio host.
  • B. David Silver
    David Silver is a leading artificial intelligence researcher best known for his work at DeepMind on reinforcement learning and the development of the AlphaGo system.
  • C. Demis Hassabis
    Demis Hassabis is a British artificial intelligence researcher, neuroscientist, and entrepreneur best known as the co-founder and CEO of DeepMind, a leading AI company acquired by Google.
  • D. Shane Legg
    Shane Legg is a computer scientist and AI researcher best known as a co-founder of DeepMind and for his influential work on artificial general intelligence.
  • E. 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.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3599daa508190a9ed6f64138c0e53 completed April 18, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ef6cbe0819081fdb3d2665fcf68 completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:16 a.m.