Triple
T19749439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yun |
E474338
|
entity |
| Predicate | nameOrderInChina |
P37983
|
FINISHED |
| Object | follows family name |
—
|
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: follows family name | Statement: [Yun, nameOrderInChina, follows family name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameOrderInChina Context triple: [Yun, nameOrderInChina, follows family name]
-
A.
nameOrderInChinese
chosen
Indicates that the entities are arranged in the order that personal names are written or spoken in Chinese (family name first, given name second).
-
B.
nameOrderInJapan
Indicates that the person’s name is written or presented in the Japanese order, with the family name appearing before the given name.
-
C.
nameInChinese
Indicates that an entity has a specific written name or label expressed in the Chinese language.
-
D.
fullNameInChineseGivenName
Indicates that the entity’s full name, when written in Chinese, is ordered with the given name first.
-
E.
rankingByLengthInChina
Indicates that entities are ordered or evaluated based on their length within the context of China.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65296fa80819085aa4a18153531cf |
completed | April 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.