Triple
T32799870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guanyu |
E838867
|
entity |
| Predicate | courtesyNameInChinese |
P83784
|
FINISHED |
| Object | 雲長 |
—
|
NE NERFINISHED |
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: 雲長 | Statement: [Guanyu, courtesyNameInChinese, 雲長]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtesyNameInChinese Context triple: [Guanyu, courtesyNameInChinese, 雲長]
-
A.
courtesyNameChinese
chosen
Indicates that one entity is the Chinese courtesy name (zì) traditionally adopted by a person, typically in adulthood, as an alternative to their given name.
-
B.
nameInChinese
Indicates that an entity has a specific written name or label expressed in the Chinese language.
-
C.
fullNameInChineseGivenName
Indicates that the entity’s full name, when written in Chinese, is ordered with the given name first.
-
D.
nameOrderInChinese
Indicates that the entities are arranged in the order that personal names are written or spoken in Chinese (family name first, given name second).
-
E.
correspondsToChineseSurname
Indicates that one entity is the Chinese surname equivalent or counterpart of another 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_69f3493c7f6881908edf2aa13631d1e0 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:14 a.m.