Triple
T20566389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nguyen Vietnam |
E504975
|
entity |
| Predicate | hasCivilServiceExamsBasedOn |
P66416
|
FINISHED |
| Object | Confucian classics |
—
|
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: Confucian classics | Statement: [Nguyen Vietnam, hasCivilServiceExamsBasedOn, Confucian classics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCivilServiceExamsBasedOn Context triple: [Nguyen Vietnam, hasCivilServiceExamsBasedOn, Confucian classics]
-
A.
hasNotableFieldOfBoardExams
Indicates that an entity (such as a person or organization) is associated with a specific notable field or subject area in which board examinations are taken or administered.
-
B.
workExamined
Indicates that one entity has examined, reviewed, or studied the work produced by another entity.
-
C.
writtenExamSubjectsInclude
chosen
Indicates that the set of subjects specified is included among the subjects covered by a particular written exam.
-
D.
passedExam
Indicates that an entity has successfully met the required criteria to pass a particular exam.
-
E.
writtenExamRequiredBefore
Indicates that completing a written exam is a prerequisite that must occur before another specified action or event.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a7a228948190b47a3a61f239e00d |
completed | April 20, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:39 a.m.