Triple
T9888791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vice President of China |
E181404
|
entity |
| Predicate | officeHolderTitleInChinese |
P91623
|
FINISHED |
| Object | 中华人民共和国副主席 |
—
|
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: 中华人民共和国副主席 | Statement: [Vice President of China, officeHolderTitleInChinese, 中华人民共和国副主席]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderTitleInChinese Context triple: [Vice President of China, officeHolderTitleInChinese, 中华人民共和国副主席]
-
A.
officeHolderTitleInJapanese
Indicates the official title or designation of an office holder as expressed in the Japanese language.
-
B.
officeHolderTitleInKorean
Indicates the official title or designation of an office holder as expressed in the Korean language.
-
C.
officeHolderTitle
Indicates the official position or title held by a person in an office or role.
-
D.
officeHolderTitleInThai
Indicates the official title or designation of an office holder as expressed in the Thai language.
-
E.
officeHolderTitleInLatin
Indicates that the specified office holder’s title is expressed in its Latin-language form.
- 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_69ca8283a6708190801af7a25a7ebb9f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb47be2988190811a99dc56ae542a |
completed | April 2, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69cd1d810ed48190a252b70e9390c8f3 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd36f112bc81908b473787e702de2f |
completed | April 1, 2026, 3:17 p.m. |
Created at: March 30, 2026, 8:39 p.m.