Triple

T1668677
Position Surface form Disambiguated ID Type / Status
Subject Data Control Language E36072 entity
Predicate implementedBy P172 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: [Data Control Language, implementedBy, MariaDB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MariaDB
Context triple: [Data Control Language, implementedBy, 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. 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.
  • D. PostgreSQL
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • E. DB
    DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
  • 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90adf3d3c81909233e574e79b82a2 completed March 5, 2026, 4:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad71b0cde08190a210cf387459e9ad completed March 8, 2026, 12:55 p.m.
Created at: March 4, 2026, 7:29 p.m.