Triple

T16850199
Position Surface form Disambiguated ID Type / Status
Subject Alphabet Other Bets E409654 entity
Predicate includesBusiness P110112 FINISHED
Object CapitalG E35322 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: CapitalG | Statement: [Alphabet Other Bets, includesBusiness, CapitalG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CapitalG
Context triple: [Alphabet Other Bets, includesBusiness, CapitalG]
  • A. CapitalG chosen
    CapitalG is Alphabet Inc.’s independent growth equity investment fund that backs later-stage technology companies.
  • B. Capital
    Capital is Karl Marx’s foundational critique of the capitalist economic system, analyzing its structures, dynamics, and inherent contradictions.
  • C. Track Capital of the World
    Track Capital of the World is a nickname highlighting Fayetteville, Arkansas’s prominence and success in collegiate track and field.
  • D. Reading Capital
    Reading Capital is a seminal Marxist philosophical text in which Louis Althusser and collaborators offer a structuralist reinterpretation of Karl Marx’s Capital.
  • E. Insurance Capital of the World
    Insurance Capital of the World is a nickname for Hartford, Connecticut, reflecting its historic and ongoing prominence as a major center of the insurance industry.
  • 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b378dda48190ab81d75f2cfe3ab3 completed April 18, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb1f02648190937c692af83843dc completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:24 a.m.