Triple
T105560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanji |
E2128
|
entity |
| Predicate | hasDigitalEncoding |
P5799
|
FINISHED |
| Object | Unicode Han characters |
—
|
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: Unicode Han characters | Statement: [Kanji, hasDigitalEncoding, Unicode Han characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDigitalEncoding Context triple: [Kanji, hasDigitalEncoding, Unicode Han characters]
-
A.
hasDigitalArchive
Indicates that an entity maintains or is associated with a collection of materials stored in a digital archive.
-
B.
hasDigitalLibrary
Indicates that an entity maintains or provides access to a collection of digital resources or publications.
-
C.
isAnalogOrDigital
Indicates whether something operates using analog signals/representation or digital signals/representation.
-
D.
hasDigitalCollections
Indicates that an entity possesses or provides access to one or more collections of materials in digital form.
-
E.
hasDigitalInitiative
Indicates that an entity is engaged in or associated with a specific digital project, program, or transformation effort.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25711f6788190a22252ea3a3af394 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563be81c81908ccc5ed44edd6b8e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2570f45bc81909ebba7ee5f602976 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.