Triple
T7947111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 双一流 |
E184523
|
entity |
| Predicate | 相关概念 |
P55522
|
FINISHED |
| Object | 一流大学 |
—
|
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: 一流大学 | Statement: [双一流, 相关概念, 一流大学]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 相关概念 Context triple: [双一流, 相关概念, 一流大学]
-
A.
definitionOfRelatedConcept
Indicates that one concept provides the formal meaning, explanation, or characterization of another closely related concept.
-
B.
関連主題
chosen
Indicates that there exists a thematically or contextually related subject connected to the given entity.
-
C.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
D.
hasConceptualParallel
Indicates that one entity corresponds to or mirrors another at a conceptual level, showing a similar idea, structure, or pattern despite possible differences in form or context.
-
E.
conceptuallyDependsOn
Indicates that one entity’s definition, validity, or understanding relies on or is grounded in the concepts provided by another entity.
- 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b2abdbc819085ae53826d36af3b |
completed | March 31, 2026, 3:10 a.m. |
| PD | Predicate disambiguation | batch_69cae9361bc48190886b7681e563d46b |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:09 p.m.