Triple

T15264008
Position Surface form Disambiguated ID Type / Status
Subject Vyper E364852 entity
Predicate abbreviation P43 FINISHED
Object Vyper language E364852 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: Vyper language | Statement: [Vyper, abbreviation, Vyper language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vyper language
Context triple: [Vyper, abbreviation, Vyper language]
  • A. Vyper chosen
    Vyper is a Pythonic, security-focused programming language used to write smart contracts on the Ethereum blockchain.
  • B. PyTeal
    PyTeal is a Python language binding and framework for writing Algorand smart contracts that compile down to the blockchain’s native TEAL bytecode.
  • C. Solidity
    Solidity is a statically-typed, contract-oriented programming language primarily used to write and deploy smart contracts on the Ethereum platform and compatible blockchains.
  • D. Ethereum Virtual Machine
    The Ethereum Virtual Machine is a decentralized, sandboxed runtime that executes smart contracts and enforces the rules of the Ethereum blockchain across a global network of nodes.
  • E. Vale programming language
    Vale is a memory-safe, performance-focused systems programming language that explores region-based memory management and borrow-checking concepts similar to those in Rust.
  • 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0084fed0481908e452c89cba2be82 completed April 15, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69feef6fc290819096ef03f8ecae8876 completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:14 a.m.