Triple
T10168079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OER |
E235256
|
entity |
| Predicate | encodingBasis |
P28140
|
FINISHED |
| Object | octet-based binary format |
—
|
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: octet-based binary format | Statement: [OER, encodingBasis, octet-based binary format]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encodingBasis Context triple: [OER, encodingBasis, octet-based binary format]
-
A.
encodingBasisFor
Indicates that one encoding scheme serves as the foundational or reference basis for defining or interpreting another encoding.
-
B.
encodes
Indicates that one entity contains or represents the information, instructions, or structure of another in a coded or symbolic form.
-
C.
encodingLibrary
Indicates that one entity is the software library or tool used to encode, transform, or serialize the other entity’s data or content.
-
D.
encodedIn
Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
-
E.
encodingStructure
chosen
Indicates the structural scheme or format used to encode information or data.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec6f64a48190883aefce58a65ca6 |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.