Triple
T8289612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AVI |
E193860
|
entity |
| Predicate | encodingIndependence |
P82555
|
FINISHED |
| Object | codec-agnostic container |
—
|
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: codec-agnostic container | Statement: [AVI, encodingIndependence, codec-agnostic container]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encodingIndependence Context triple: [AVI, encodingIndependence, codec-agnostic container]
-
A.
isLanguageIndependent
Indicates that the relationship, property, or behavior holds true regardless of the specific natural language used to express or encode it.
-
B.
supportsUnicode
Indicates that an entity is capable of correctly handling, storing, or displaying Unicode-encoded text.
-
C.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
-
D.
usesCharacterSet
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
E.
codingSystemType
Indicates the classification or category of coding system used to encode or represent information in a given context.
- F. None of above. chosen
Provenance (4 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_69ca82e32db481908b72f3804fa71152 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7c99fdd48190a3f304237be609a0 |
completed | March 31, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:52 p.m.