Triple
T34152368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wenzhou-Kean University campus |
E876033
|
entity |
| Predicate | countryOfPartnerInstitution |
P308
|
FINISHED |
| Object | United States of America |
—
|
NE NERFINISHED |
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: United States of America | Statement: [Wenzhou-Kean University campus, countryOfPartnerInstitution, United States of America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfPartnerInstitution Context triple: [Wenzhou-Kean University campus, countryOfPartnerInstitution, United States of America]
-
A.
countryOfInstitution
chosen
Indicates the country in which an institution is located or officially based.
-
B.
countryPartner
Indicates a formal partnership relationship between two countries, such as cooperation, alliance, or strategic collaboration.
-
C.
countryOfParentOrganization
Indicates that an organization is located in or associated with the country where its parent organization is based.
-
D.
countryOfParticipant
Indicates the country with which a given participant is associated or from which they originate in the context of an event or activity.
-
E.
collaborationCountry
Indicates that there is a collaborative relationship or joint activity involving entities associated with the specified country.
- 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_69f349abaa508190a820f206620efddc |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a01295195748190b896d99c3d1f6134 |
completed | May 11, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_6a0128fe96dc8190a73715ab08752dd1 |
completed | May 11, 2026, 12:55 a.m. |
Created at: May 1, 2026, 1:54 a.m.