Triple
T10032291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | If-None-Match |
E204878
|
entity |
| Predicate | cacheBenefit |
P49949
|
FINISHED |
| Object | reduces bandwidth usage |
—
|
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: reduces bandwidth usage | Statement: [If-None-Match, cacheBenefit, reduces bandwidth usage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cacheBenefit Context triple: [If-None-Match, cacheBenefit, reduces bandwidth usage]
-
A.
caches
Indicates that one entity stores data or resources so they can be quickly retrieved for future use by another entity or process.
-
B.
cacheType
Indicates the specific kind or category of cache associated with an entity or operation.
-
C.
supportsDynamicCaching
Indicates that an entity is capable of enabling or handling caching behavior that can change or be configured dynamically at runtime.
-
D.
benefice
Indicates that one entity grants or bestows a benefit, favor, or advantage upon another.
-
E.
expectedBenefit
chosen
Indicates the benefit or positive outcome that is anticipated to result from a particular action, decision, or relationship between entities.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdce461d6481908cc8f968856e0337 |
completed | April 2, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69cd4b8638508190b22acc65500ec7d6 |
completed | April 1, 2026, 4:44 p.m. |
Created at: March 30, 2026, 8:54 p.m.