Triple
T20566263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vietnamese imperial examination system |
E504972
|
entity |
| Predicate | highestDegreeTitle |
P112032
|
FINISHED |
| Object | Tiến sĩ |
—
|
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: Tiến sĩ | Statement: [Vietnamese imperial examination system, highestDegreeTitle, Tiến sĩ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highestDegreeTitle Context triple: [Vietnamese imperial examination system, highestDegreeTitle, Tiến sĩ]
-
A.
hasHighestDegreeTitle
chosen
Indicates that one entity holds the most advanced or highest-ranking academic degree title associated with another entity.
-
B.
hasHighestDegree
Indicates that one entity possesses the highest academic degree attained by another entity.
-
C.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
D.
hasHighestRegularDegree
Indicates that the subject has the greatest regular (non-irregular or non-special) degree value among a set of comparable entities.
-
E.
eligibleDegree
Indicates that an academic degree qualifies its holder to be considered eligible for a particular program, position, or requirement.
- 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.