Triple
T5232846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese imperial examination system |
E118150
|
entity |
| Predicate | highestDegree |
P6
|
FINISHED |
| Object | jinshi |
—
|
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: jinshi | Statement: [Chinese imperial examination system, highestDegree, jinshi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highestDegree Context triple: [Chinese imperial examination system, highestDegree, jinshi]
-
A.
academicDegree
chosen
Indicates that an entity holds or has been awarded a specific academic degree.
-
B.
hasHighestRegularDegree
Indicates that the subject has the greatest regular (non-irregular or non-special) degree value among a set of comparable entities.
-
C.
eligibleDegree
Indicates that an academic degree qualifies its holder to be considered eligible for a particular program, position, or requirement.
-
D.
hasHigherDegree
Indicates that one entity possesses an academic degree that is of a higher level than the academic degree held by another entity.
-
E.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
- 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b0389048190b55b7c44fe657044 |
completed | March 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69bd77bf1ef08190bb3487b3f3ee088c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:49 p.m.