Triple
T28818920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Goujian of Yue |
E727705
|
entity |
| Predicate | associatedIdiom |
P183867
|
FINISHED |
| Object | 臥薪嘗膽 |
—
|
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: 臥薪嘗膽 | Statement: [King Goujian of Yue, associatedIdiom, 臥薪嘗膽]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedIdiom Context triple: [King Goujian of Yue, associatedIdiom, 臥薪嘗膽]
-
A.
hasIdiom
chosen
Indicates that one entity is an idiomatic expression associated with, or used to represent, the meaning or concept of another entity.
-
B.
associatedProverb
Indicates that there is a relationship between something (such as a concept, situation, or statement) and a specific proverb that is linked to or expressive of it.
-
C.
pairedWithIdiomatically
Indicates that one entity is commonly or conventionally paired with another in idiomatic usage or expression.
-
D.
relatedProverb
Indicates that one entity is a proverb that is thematically or conceptually related to another entity.
-
E.
associatedWithVerb
Indicates that one entity is connected or linked to another through some verb-based relationship or action.
- 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_69f0319d09088190bbf14cdf1987792a |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_6a01e4ba62748190a4756689219b6269 |
completed | May 11, 2026, 2:16 p.m. |
| PD | Predicate disambiguation | batch_6a01e3fc2d908190a075c7c1549e5640 |
completed | May 11, 2026, 2:13 p.m. |
Created at: April 28, 2026, 6:33 a.m.