Triple
T8486607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accept-Language |
E200846
|
entity |
| Predicate | exampleValue |
P7345
|
FINISHED |
| Object | Accept-Language: en-US,en;q=0.9,fr;q=0.8 |
—
|
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: Accept-Language: en-US,en;q=0.9,fr;q=0.8 | Statement: [Accept-Language, exampleValue, Accept-Language: en-US,en;q=0.9,fr;q=0.8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleValue Context triple: [Accept-Language, exampleValue, Accept-Language: en-US,en;q=0.9,fr;q=0.8]
-
A.
exampleType
Indicates that one entity serves as a representative or illustrative instance of the type or category defined by another entity.
-
B.
exampleWord
Indicates that one entity serves as an illustrative or representative instance of another entity or concept.
-
C.
value
chosen
Indicates that one entity possesses, represents, or corresponds to a particular quantity, quality, or assigned worth.
-
D.
exampleTopic
Indicates that something serves as an illustrative or representative instance of a broader topic or concept.
-
E.
exampleApplication
Indicates that something serves as a representative or illustrative instance of how an application is used or functions.
- 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.