Triple
T817000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PostgreSQL |
E17669
|
entity |
| Predicate | supportsDataModel |
P203
|
FINISHED |
| Object | relational model |
—
|
LITERAL 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: relational model | Statement: [PostgreSQL, supportsDataModel, relational model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsDataModel Context triple: [PostgreSQL, supportsDataModel, relational model]
-
A.
dataModel
Indicates a relationship where an entity defines, uses, or is structured according to a specific data model or schema.
-
B.
supportsDatastoreType
Indicates that one entity is capable of working with, handling, or being compatible with a specified type of datastore.
-
C.
supportsMultipleDataAndDisplayProtocols
Indicates that an entity is capable of handling more than one type of data protocol and more than one type of display protocol.
-
D.
supportsFeature
chosen
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
E.
supportsField
Indicates that one entity provides the necessary structure, stability, or backing for a particular field, area, or domain associated with another entity.
- F. None of above.
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_69a4ab621d2c819083f10bff4f66c482 |
completed | March 1, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69a4aa756920819080ae82948974c876 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.