Triple

T1634810
Position Surface form Disambiguated ID Type / Status
Subject AppSheet E35336 entity
Predicate supportsDataSource P24486 FINISHED
Object PostgreSQL databases E17669 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: PostgreSQL databases | Statement: [AppSheet, supportsDataSource, PostgreSQL databases]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PostgreSQL databases
Context triple: [AppSheet, supportsDataSource, PostgreSQL databases]
  • A. PostgreSQL chosen
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • B. PostGIS
    PostGIS is an open-source spatial database extender that adds robust geographic object support and spatial querying capabilities to PostgreSQL.
  • C. DB
    DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
  • D. Amazon Redshift
    Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
  • E. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • 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_69a886036bc081909ff5de16dbe5e8ea completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61e142ac8190aa2fbd8f0826b5b2 completed March 6, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58d9db5c819081408977834ad606 completed March 8, 2026, 11:09 a.m.
Created at: March 4, 2026, 7:28 p.m.