Triple
T14370794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DAViCal |
E356352
|
entity |
| Predicate | dataStorage |
P1596
|
FINISHED |
| Object | PostgreSQL database |
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 database | Statement: [DAViCal, dataStorage, PostgreSQL database]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PostgreSQL database Context triple: [DAViCal, dataStorage, PostgreSQL database]
-
A.
PostgreSQL
chosen
PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
-
B.
PostgreSQL documentation
PostgreSQL documentation is the official, comprehensive reference and user guide for the PostgreSQL relational database system, covering its features, configuration, and extensions.
-
C.
Greenplum
Greenplum is a massively parallel, open-source data warehouse and analytics platform designed for large-scale business intelligence and big data workloads.
-
D.
PostGIS
PostGIS is an open-source spatial database extender that adds robust geographic object support and spatial querying capabilities to PostgreSQL.
-
E.
PolarDB
PolarDB is a cloud-native relational database service developed by Alibaba Cloud that provides high performance, scalability, and compatibility with popular database engines.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8fb2082c8190b42cc5f2bab4f574 |
completed | April 14, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd550e677c8190837c3b9ccb64f0cd |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:15 a.m.