Triple
T32498407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JWE |
E830586
|
entity |
| Predicate | compactSerializationStructure |
P28140
|
FINISHED |
| Object | five dot-separated Base64URL-encoded parts |
—
|
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: five dot-separated Base64URL-encoded parts | Statement: [JWE, compactSerializationStructure, five dot-separated Base64URL-encoded parts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compactSerializationStructure Context triple: [JWE, compactSerializationStructure, five dot-separated Base64URL-encoded parts]
-
A.
serialStructure
Indicates a relationship where components are arranged or connected in a sequential, one-after-another order, such that each element follows the previous in a linear chain.
-
B.
encodingStructure
chosen
Indicates the structural scheme or format used to encode information or data.
-
C.
serialized
Indicates that one entity has been converted into a sequential, storable or transmittable data format representing its structure or state.
-
D.
originalSerialization
Indicates that one entity is the initial or source serialized form from which another serialized representation is derived.
-
E.
compressionFunctionStructure
Indicates the structural or organizational characteristics that define how a compression function is composed or implemented.
- 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_69f349219cb8819087e120f509629c1b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 1, 2026, 12:59 a.m.