Triple
T6469960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East_Asian_Width |
E142322
|
entity |
| Predicate | categoryLabel_F |
P26507
|
FINISHED |
| Object | Fullwidth |
—
|
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: Fullwidth | Statement: [East_Asian_Width, categoryLabel_F, Fullwidth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: categoryLabel_F Context triple: [East_Asian_Width, categoryLabel_F, Fullwidth]
-
A.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
B.
categoryConcept
Indicates that one entity serves as a categorical type or conceptual class under which the other entity is grouped or classified.
-
C.
coreCategory
Indicates that one entity is the primary or fundamental category to which another entity belongs or is classified under.
-
D.
categoryFocus
Indicates that one entity is the primary subject, theme, or focal point within the broader category defined by the other entity.
-
E.
labelCatalog
chosen
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
- 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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a2e896481908ed004e3b0a33121 |
completed | March 22, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:50 p.m.