Triple

T4278949
Position Surface form Disambiguated ID Type / Status
Subject Michael Widenius E97105 entity
Predicate notableWork P4 FINISHED
Object MariaDB E36148 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: MariaDB | Statement: [Michael Widenius, notableWork, MariaDB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MariaDB
Context triple: [Michael Widenius, notableWork, MariaDB]
  • A. MariaDB chosen
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • B. MySQL
    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.
  • C. MariaDB Foundation
    MariaDB Foundation is a non-profit organization that oversees the development, governance, and community ecosystem of the open-source MariaDB database.
  • D. TokuDB
    TokuDB is a high-performance storage engine for MySQL and MariaDB designed for large-scale, write-intensive workloads using Fractal Tree indexing to improve compression and insertion speed.
  • E. MySQL HeatWave
    MySQL HeatWave is a fully managed, in-memory query acceleration and analytics engine integrated with MySQL to deliver high-performance OLTP and OLAP processing on the same database service.
  • 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_69b350201ac88190b9d8980da5f0d03d completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b708b481908c1683741f84ee55 completed March 14, 2026, 7:32 p.m.
Created at: March 12, 2026, 11:07 p.m.