Triple

T7938611
Position Surface form Disambiguated ID Type / Status
Subject Katello E184339 entity
Predicate usesDatabase P11852 FINISHED
Object PostgreSQL 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 | Statement: [Katello, usesDatabase, PostgreSQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PostgreSQL
Context triple: [Katello, usesDatabase, PostgreSQL]
  • A. PostgreSQL chosen
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • B. Greenplum
    Greenplum is a massively parallel, open-source data warehouse and analytics platform designed for large-scale business intelligence and big data workloads.
  • C. PostgreSQL documentation
    PostgreSQL documentation is the official, comprehensive reference and user guide for the PostgreSQL relational database system, covering its features, configuration, and extensions.
  • D. PolarDB
    PolarDB is a cloud-native relational database service developed by Alibaba Cloud that provides high performance, scalability, and compatibility with popular database engines.
  • E. PostGIS
    PostGIS is an open-source spatial database extender that adds robust geographic object support and spatial querying capabilities to PostgreSQL.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3af0a2048190838d1aeda59fda0b completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63ad5fbc819082f7900cd618bd0e completed April 1, 2026, 12:15 a.m.
Created at: March 30, 2026, 5:08 p.m.