Triple
T5479478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OSPF |
E123434
|
entity |
| Predicate | convergenceType |
P14357
|
FINISHED |
| Object | fast |
—
|
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: fast | Statement: [OSPF, convergenceType, fast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: convergenceType Context triple: [OSPF, convergenceType, fast]
-
A.
convergenceProperty
chosen
Indicates that one entity has a convergence-related characteristic or behavior with respect to another entity, such as approaching a limit or stabilizing under repeated application.
-
B.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
C.
optimizationType
Indicates the specific strategy or method used to improve performance or efficiency within a given process or system.
-
D.
derivationType
Indicates the specific manner or process by which one entity is derived or obtained from another.
-
E.
calculationType
Indicates the specific method, formula, or approach used to perform a calculation in the described relationship.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9248ca348190aa116cace0f9b07a |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd91a58c448190904964a439045e05 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.