Triple

T816286
Position Surface form Disambiguated ID Type / Status
Subject Django E17657 entity
Predicate supportsDatabase P11254 FINISHED
Object SQLite E36073 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: SQLite | Statement: [Django, supportsDatabase, SQLite]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SQLite
Context triple: [Django, supportsDatabase, SQLite]
  • A. SQLite chosen
    SQLite is a lightweight, self-contained, serverless SQL database engine widely embedded in applications, operating systems, and devices.
  • B. SQL
    SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
  • C. PostgreSQL
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • D. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • E. ODBC
    ODBC (Open Database Connectivity) is a standard API that enables applications to access and query data from a wide variety of relational and non-relational database management systems using a common interface.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4b2b503d48190bd4f33548a22d5fe completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8d1a448190be8494fa2776615a completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:38 p.m.