Triple
T31943578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor of Jiangsu |
E815587
|
entity |
| Predicate | officeLevelInChina |
P111950
|
FINISHED |
| Object | provincial-ministerial level |
—
|
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: provincial-ministerial level | Statement: [Governor of Jiangsu, officeLevelInChina, provincial-ministerial level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeLevelInChina Context triple: [Governor of Jiangsu, officeLevelInChina, provincial-ministerial level]
-
A.
roleInChina
Indicates that one entity holds or performs a specific role, position, or function within the context of China.
-
B.
rankInChineseAdministrativeHierarchy
chosen
Indicates the relative level or position an administrative unit holds within the formal hierarchy of Chinese government administration.
-
C.
officeNameInChinese
Indicates that an entity’s office name is expressed in the Chinese language.
-
D.
officeHolderTitleInPinyin
Indicates the pinyin (romanized Chinese) form of the title held by an office holder.
-
E.
officeHolderTitleInChinese
Indicates the Chinese-language title or designation held by an office holder in a given position or role.
- 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_69f348f42d188190a33fc8d20ec50517 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fefb15220081908da36aac386fa582 |
completed | May 9, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69fefa8e8ad48190a723fed81e9d64d0 |
completed | May 9, 2026, 9:12 a.m. |
Created at: May 1, 2026, 12:06 a.m.