Triple

T11003405
Position Surface form Disambiguated ID Type / Status
Subject Łukasz Kaiser E260054 entity
Predicate employer P7 FINISHED
Object Google Research E46728 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: Google Research | Statement: [Łukasz Kaiser, employer, Google Research]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Google Research
Context triple: [Łukasz Kaiser, employer, Google Research]
  • A. Google Research chosen
    Google Research is the research division of Google focused on advancing the state of the art in computer science and artificial intelligence through fundamental and applied research.
  • B. Google X
    Google X is a semi-secret research and development lab of Google (now Alphabet) focused on creating breakthrough technologies such as autonomous vehicles and other ambitious "moonshot" projects.
  • C. Google Brain
    Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
  • D. Microsoft Research
    Microsoft Research is the research division of Microsoft, dedicated to advancing computer science and related fields through fundamental and applied research.
  • E. Microsoft Research Cambridge
    Microsoft Research Cambridge is a leading European research laboratory of Microsoft focused on advancing computer science and related fields through fundamental and applied research.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797546f448190946ee6442d657dc5 completed April 9, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3453d181081908cb58a957f4d1295 completed April 18, 2026, 8:47 a.m.
Created at: April 8, 2026, 9:25 p.m.