Triple
T1866804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BOOTP |
E34939
|
entity |
| Predicate | usesClientServerModel |
P9933
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [BOOTP, usesClientServerModel, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesClientServerModel Context triple: [BOOTP, usesClientServerModel, yes]
-
A.
usesBusinessModel
Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
-
B.
concurrentModel
Indicates that two or more processes, activities, or states occur or are valid at the same time, potentially interacting or overlapping in execution.
-
C.
hasClient
Indicates that an entity maintains a client relationship with another entity, typically as a provider of goods or services.
-
D.
hasServer
chosen
Indicates that one entity functions as or possesses a server that provides services or resources to another entity.
-
E.
usedProgramModel
Indicates that an entity employed a specific program model as the basis or framework for its activities or operations.
- 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_69a88600b2f88190bc09303e68ab517e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abb16c09e48190a345c95eab59fd87 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe02c3c819093a4744b476106ca |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.