Triple
T31992143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 晏 |
E816899
|
entity |
| Predicate | usedInClassicalChinese |
P195280
|
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: [晏, usedInClassicalChinese, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInClassicalChinese Context triple: [晏, usedInClassicalChinese, yes]
-
A.
differenceFromClassicalChinese
Indicates a relationship where something is characterized by how it diverges or differs from Classical Chinese in form, usage, or features.
-
B.
usedChineseCharacters
Indicates that one entity employed or wrote using Chinese characters in relation to another entity or context.
-
C.
hasMeaningInChinese
Indicates that one entity (such as a word, phrase, or symbol) possesses a specific meaning or interpretation within the Chinese language.
-
D.
knownToAncientChinese
Indicates that something was recognized, identified, or understood by people in ancient Chinese civilizations.
-
E.
usedInCulture
Indicates that something (such as an object, practice, or concept) is employed, referenced, or plays a role within a particular culture or cultural context.
- 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_69f348f8002081909a3588758ba94afb |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fdb45537288190b6791078d4a6899f |
completed | May 8, 2026, 10 a.m. |
| PD | Predicate disambiguation | batch_69fdb39ad96481908376d7def9fafc13 |
completed | May 8, 2026, 9:57 a.m. |
| PDg | Predicate description generation | batch_69fdb4544b548190b8971f8055d48caa |
completed | May 8, 2026, 10 a.m. |
Created at: May 1, 2026, 12:13 a.m.