Triple
T28628994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese Wikisource |
E724592
|
entity |
| Predicate | supportsVariantConversion |
P14330
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Chinese Wikisource, supportsVariantConversion, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsVariantConversion Context triple: [Chinese Wikisource, supportsVariantConversion, yes]
-
A.
allowsConversionTo
Indicates that one entity permits or enables transformation or change into another specified form or state.
-
B.
acceptsConversionFrom
chosen
Indicates that one entity can validly receive or handle a conversion from another entity’s type, format, or representation.
-
C.
supportsModelVariant
Indicates that one entity is capable of operating with, being compatible with, or otherwise accommodating a specific variant of a model.
-
D.
someVariantsConvertedTo
Indicates that certain variants of an entity have been transformed or converted into another form or set of variants.
-
E.
methodOfConversion
Indicates the specific process or technique used to transform one form, state, or representation into 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_69f01d822ac08190932de59ec2268ed2 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_6a019579463c8190b51e39183b57bbaf |
completed | May 11, 2026, 8:38 a.m. |
| PD | Predicate disambiguation | batch_6a0192d309488190a3d86c93e7138c77 |
completed | May 11, 2026, 8:26 a.m. |
Created at: April 28, 2026, 4:37 a.m.