Triple
T37163797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EBML |
E920742
|
entity |
| Predicate | valueEncoding |
P33682
|
FINISHED |
| Object | binary data |
—
|
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: binary data | Statement: [EBML, valueEncoding, binary data]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: valueEncoding Context triple: [EBML, valueEncoding, binary data]
-
A.
dataEncodingMethod
chosen
Indicates the specific technique or format used to encode data for storage, transmission, or processing.
-
B.
encodes
Indicates that one entity contains or represents the information, instructions, or structure of another in a coded or symbolic form.
-
C.
encodedIn
Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
-
D.
encodingIs
Indicates that one entity serves as the specific encoding or coded representation of another entity.
-
E.
encodingAbstraction
Indicates an abstraction relationship where one representation or model encodes, summarizes, or symbolically captures the structure or information content of another.
- 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_69f76ea0429081908c711b55599eac3c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.