Triple

T4275323
Position Surface form Disambiguated ID Type / Status
Subject actix-web E97035 entity
Predicate repositoryName P31030 FINISHED
Object actix-web E97035 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: actix-web | Statement: [actix-web, repositoryName, actix-web]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: actix-web
Context triple: [actix-web, repositoryName, actix-web]
  • A. actix-web chosen
    actix-web is a powerful, asynchronous web framework for the Rust programming language, known for its high performance and strong type safety.
  • B. tokio
    Tokio is a popular asynchronous runtime and ecosystem for the Rust programming language, providing tools for writing fast, reliable, non-blocking applications.
  • C. wasi-http
    wasi-http is a WebAssembly System Interface (WASI) proposal that defines standardized APIs for performing HTTP operations from WebAssembly modules in a secure, host-agnostic way.
  • D. ASGI
    ASGI (Asynchronous Server Gateway Interface) is a Python standard for asynchronous web servers and applications that enables high-performance, concurrent web frameworks and services.
  • E. Uvicorn
    Uvicorn is a high-performance, ASGI-compatible web server implementation for Python, commonly used to run modern async frameworks and applications.
  • 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3501c35688190a7d15d904f15f968 completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b0b2ec819090ccf042917ae207 completed March 14, 2026, 7:32 p.m.
Created at: March 12, 2026, 11:07 p.m.