Triple

T1368274
Position Surface form Disambiguated ID Type / Status
Subject Magento E30050 entity
Predicate uses P98 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: [Magento, uses, MariaDB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MariaDB
Context triple: [Magento, uses, 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_69a498f912008190a376a98b207b2071 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c2d497f88190993d16a208ced43d completed March 1, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd47f25c48190a27f87909c15d7c3 completed March 8, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:57 p.m.