Triple
T17111518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsang |
E415236
|
entity |
| Predicate | hasSimplifiedCharacter |
P78795
|
FINISHED |
| Object | 曾 |
—
|
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: 曾 | Statement: [Tsang, hasSimplifiedCharacter, 曾]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSimplifiedCharacter Context triple: [Tsang, hasSimplifiedCharacter, 曾]
-
A.
hasTraditionalCharacter
Indicates that an entity is associated with or represented by a traditional (non-simplified or historically established) written character form.
-
B.
hasMultipleChineseCharacters
Indicates that the referenced item consists of more than one Chinese character.
-
C.
hasTraditionalEnglishCharacter
Indicates that something possesses qualities, features, or style typically associated with traditional English culture or heritage.
-
D.
characterUnicodeSimplified
chosen
Indicates that one entity is the simplified-Unicode character form corresponding to another character entity.
-
E.
canRepresentMultipleChineseCharacters
Indicates that a given form (such as a sound, syllable, or written unit) is capable of corresponding to more than one distinct Chinese character.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2bab0881908339ec7fb3ebe7e9 |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.