Triple
T7936628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HCL Notes |
E184302
|
entity |
| Predicate | clientServerModel |
P35093
|
FINISHED |
| Object | Domino server and Notes client |
—
|
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: Domino server and Notes client | Statement: [HCL Notes, clientServerModel, Domino server and Notes client]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clientServerModel Context triple: [HCL Notes, clientServerModel, Domino server and Notes client]
-
A.
modelingClient
Indicates that one entity serves as a client that is being modeled or represented by another entity in a modeling context.
-
B.
clientOf
chosen
Indicates that one entity receives services or conducts business from another entity in a client–provider relationship.
-
C.
concurrentModel
Indicates that two or more processes, activities, or states occur or are valid at the same time, potentially interacting or overlapping in execution.
-
D.
typicalServer
Indicates that an entity functions as a standard or representative example of a server within a given context or system.
-
E.
networkModel
Indicates a relationship where an entity is represented or organized according to a specific network-based structure or framework.
- 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.