Triple
T32726137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 蕲春李时珍故里 |
E836806
|
entity |
| Predicate | 相关人物国籍 |
P78054
|
FINISHED |
| Object | 中国 |
—
|
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: 中国 | Statement: [蕲春李时珍故里, 相关人物国籍, 中国]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 相关人物国籍 Context triple: [蕲春李时珍故里, 相关人物国籍, 中国]
-
A.
nationalityOfPersonReferredTo
chosen
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
-
B.
associatedWithNationality
Indicates that one entity has a connection or affiliation with the nationality of another entity.
-
C.
notableRecipientNationality
Indicates that the notable recipient of something (such as an award, honor, or recognition) has a specified nationality.
-
D.
nationalityOfPersonnel
Indicates the country or countries to which the personnel involved in an activity, organization, or context belong by citizenship or national affiliation.
-
E.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
- 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_69f34935455881909088975d79460418 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c8b80b508190b03c5a5859c695fe |
completed | May 3, 2026, 4:02 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:11 a.m.