Triple
T7936643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HCL Notes |
E184302
|
entity |
| Predicate | usesDatabaseModel |
P52665
|
FINISHED |
| Object | document-oriented database |
—
|
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: document-oriented database | Statement: [HCL Notes, usesDatabaseModel, document-oriented database]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDatabaseModel Context triple: [HCL Notes, usesDatabaseModel, document-oriented database]
-
A.
useOfModel
Indicates that one entity employs, applies, or relies on a particular model for a specific purpose or task.
-
B.
usedInDatabases
chosen
Indicates that something is employed or implemented within one or more database systems or database contexts.
-
C.
hasDatabase
Indicates that an entity possesses, uses, or is associated with a specific database.
-
D.
usedByModel
Indicates that something (such as a resource, method, or component) is utilized or consumed by a particular model.
-
E.
usedToModel
Indicates that one entity serves as a model or representation for another entity, typically for purposes of analysis, simulation, or understanding.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aede3cc81908b0d3b54e68997b9 |
completed | March 31, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69cae9335f288190ba96781fd6576a2b |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:08 p.m.