Triple
T27612386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time Protocol |
E700358
|
entity |
| Predicate | requestResponseModel |
P79828
|
FINISHED |
| Object | client-server |
—
|
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: client-server | Statement: [Time Protocol, requestResponseModel, client-server]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requestResponseModel Context triple: [Time Protocol, requestResponseModel, client-server]
-
A.
requestModel
chosen
Indicates that one entity asks another entity to provide or use a specific model for a task or interaction.
-
B.
requiresResponse
Indicates that an action, event, or communication necessitates a reply or follow-up response from another party.
-
C.
requestType
Indicates the specific kind or category of request being made in an interaction or transaction.
-
D.
requestContent
Indicates that one entity asks another entity to provide specific information, data, or material.
-
E.
responseExample
Indicates that one entity serves as an illustrative or sample response corresponding to another entity (such as a prompt, question, or situation).
- 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_69ef6a4f1d9c8190b0705acda054368d |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 2:11 p.m.