Triple

T1612484
Position Surface form Disambiguated ID Type / Status
Subject Entity Framework E34642 entity
Predicate supportsDatabase P11254 FINISHED
Object PostgreSQL (via providers) 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 (via providers) | Statement: [Entity Framework, supportsDatabase, PostgreSQL (via providers)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PostgreSQL (via providers)
Context triple: [Entity Framework, supportsDatabase, PostgreSQL (via providers)]
  • 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. PL/pgSQL
    PL/pgSQL is PostgreSQL’s procedural extension of SQL that allows writing stored functions and triggers with control structures like variables, loops, and conditionals.
  • D. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • E. PL/Python
    PL/Python is a procedural language extension for PostgreSQL that allows writing database functions and triggers in the Python programming language.
  • 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9098cd03081908c67f95fd54d2071 completed March 5, 2026, 4:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51c751308190a89f6462ee365418 completed March 8, 2026, 10:39 a.m.
Created at: March 4, 2026, 7:28 p.m.