Triple
T28771975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xvid |
E726433
|
entity |
| Predicate | hasDecoder |
P64032
|
FINISHED |
| Object | Xvid decoder |
—
|
NE NERFINISHED |
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: Xvid decoder | Statement: [Xvid, hasDecoder, Xvid decoder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDecoder Context triple: [Xvid, hasDecoder, Xvid decoder]
-
A.
usesCodec
chosen
Indicates that one entity employs or relies on a specific codec to encode, decode, or process data.
-
B.
decodingMethod
Indicates the technique or process used to convert encoded or encrypted data back into its original, interpretable form.
-
C.
usesEncoder
Indicates that one entity employs or relies on an encoder component or mechanism to perform its function or process data.
-
D.
openSourceDecoder
Indicates that the decoder component is released as open-source software, allowing public access, use, modification, and distribution of its source code.
-
E.
hasCompressor
Indicates that one entity is equipped with, contains, or uses a compressor associated with it.
- 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_69f03199997c8190b6ae43fb19312443 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: April 28, 2026, 6:16 a.m.