Triple
T18411531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 南方科技大学 |
E441768
|
entity |
| Predicate | 国际合作特点 |
P14377
|
FINISHED |
| Object | 与多所世界知名大学建立合作关系 |
—
|
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: 与多所世界知名大学建立合作关系 | Statement: [南方科技大学, 国际合作特点, 与多所世界知名大学建立合作关系]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 国际合作特点 Context triple: [南方科技大学, 国际合作特点, 与多所世界知名大学建立合作关系]
-
A.
internationalContribution
Indicates that an entity provides resources, support, or participation that benefits or advances activities beyond its own country at an international level.
-
B.
cooperatesInternationallyWith
Indicates that one entity collaborates or works jointly with another entity across national borders in an international context.
-
C.
hasInternationalRelation
Indicates that one entity maintains some form of official or recognized international relationship or interaction with another entity.
-
D.
internationalPartners
chosen
Indicates that two or more entities are engaged in a formal or recognized partnership that crosses national boundaries.
-
E.
internationalAffairsFunction
Indicates a functional role or responsibility related to managing, coordinating, or influencing interactions and relationships between entities across national borders.
- 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51a24e130819082b92f98d8d5fa3c |
completed | April 19, 2026, 6:08 p.m. |
| PD | Predicate disambiguation | batch_69e469bf7f74819096a01173493412c2 |
completed | April 19, 2026, 5:35 a.m. |
Created at: April 10, 2026, 10:47 a.m.