Triple
T10032289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | If-None-Match |
E204878
|
entity |
| Predicate | effectOnGET |
P37719
|
FINISHED |
| Object | enables conditional retrieval based on ETag |
—
|
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: enables conditional retrieval based on ETag | Statement: [If-None-Match, effectOnGET, enables conditional retrieval based on ETag]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnGET Context triple: [If-None-Match, effectOnGET, enables conditional retrieval based on ETag]
-
A.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
B.
effectOnRepresentation
chosen
Indicates how one entity influences, alters, or determines the form, quality, or characteristics of another entity’s representation.
-
C.
tookEffect
Indicates that a change, rule, condition, or event became active, operative, or started producing its intended consequences.
-
D.
effectOnCampaign
Indicates the influence or impact that one factor has on the outcome or performance of a campaign.
-
E.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
- 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.