Triple
T27078919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sungkyunkwan University |
E685539
|
entity |
| Predicate | majorIndustryPartner |
P144950
|
FINISHED |
| Object | Samsung Electronics |
—
|
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: Samsung Electronics | Statement: [Sungkyunkwan University, majorIndustryPartner, Samsung Electronics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorIndustryPartner Context triple: [Sungkyunkwan University, majorIndustryPartner, Samsung Electronics]
-
A.
hasIndustryPartnerships
Indicates that an entity maintains formal collaborative or cooperative relationships with organizations in a particular industry.
-
B.
employerOrPartner
Indicates that one entity is either the employer of, or a business partner with, another entity.
-
C.
primaryPartners
chosen
Indicates that the entities are each other’s main or most significant partners in a relationship, typically implying priority or exclusivity over other partnerships.
-
D.
cooperationPartner
Indicates that two entities are engaged in a collaborative relationship, working together toward shared goals or mutual benefit.
-
E.
isPartOfIndustry
Indicates that one entity belongs to, operates within, or is categorized under a particular industry sector.
- 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_69ef14843b1481909d828b3d5a44550a |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: April 27, 2026, 8:33 a.m.