Triple

T17499337
Position Surface form Disambiguated ID Type / Status
Subject Presto E426151 entity
Predicate canQuery P9928 FINISHED
Object MySQL NE NERFINISHED

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: MySQL | Statement: [Presto, canQuery, MySQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MySQL
Context triple: [Presto, canQuery, MySQL]
  • A. MySQL chosen
    MySQL is a widely used open-source relational database management system known for its reliability, performance, and role in powering many web applications and services.
  • B. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • C. MySQL AB
    MySQL AB was the Swedish company that developed and commercially supported the popular open-source MySQL relational database management system.
  • D. Percona XtraDB
    Percona XtraDB is an enhanced, high-performance fork of the InnoDB storage engine used in MySQL and MariaDB, optimized for improved scalability, reliability, and performance.
  • E. Percona Server for MySQL
    Percona Server for MySQL is an enhanced, open-source drop-in replacement for MySQL designed for improved performance, scalability, and reliability in demanding database environments.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4521028048190aa7c4023a72a12f4 completed April 19, 2026, 3:54 a.m.
Created at: April 10, 2026, 5:48 a.m.