Triple
T17026265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tan (談) |
E413070
|
entity |
| Predicate | strokeCountSimplified |
P58361
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Tan (談), strokeCountSimplified, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: strokeCountSimplified Context triple: [Tan (談), strokeCountSimplified, 10]
-
A.
hasStrokeCount
chosen
Indicates the number of strokes required to write a given symbol or character.
-
B.
hasStrokeCountApprox
Indicates an approximate number of strokes associated with writing or drawing the related entity.
-
C.
radicalStrokeCount
Indicates the number of strokes used to write the radical component of a character.
-
D.
hasStrokeOrder
Indicates that there is a specific, ordered sequence of strokes used to write or draw the related symbol or character.
-
E.
characterUnicodeSimplified
Indicates that one entity is the simplified-Unicode character form corresponding to another character entity.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d46a5081908bc5681621dd8534 |
completed | April 18, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.