Triple
T8486568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accept-Encoding |
E200845
|
entity |
| Predicate | semantics |
P28757
|
FINISHED |
| Object | q=0 means encoding is not acceptable |
—
|
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: q=0 means encoding is not acceptable | Statement: [Accept-Encoding, semantics, q=0 means encoding is not acceptable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: semantics Context triple: [Accept-Encoding, semantics, q=0 means encoding is not acceptable]
-
A.
semanticRootMeaning
Indicates the fundamental or core meaning that underlies a word, phrase, or expression in a semantic structure.
-
B.
hasSemanticsDefinedBy
Indicates that the meaning or interpretation of one entity is specified, constrained, or determined by another entity.
-
C.
hasSemantics
chosen
Indicates that one entity carries or encodes the meaning, interpretation, or semantic content associated with another entity.
-
D.
linguisticSignificance
Indicates the degree to which something is important, influential, or meaningful within a particular language or linguistic system.
-
E.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
- 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_69ca831d7b148190a6e32c1de43ab13b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53c4d608190a766c0e919a4b96f |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd107633c8190a36ba50e07876918 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:13 p.m.