Triple
T1856530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Algonquin College |
E41716
|
entity |
| Predicate | hasIndustryPartnerships |
P33627
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Algonquin College, hasIndustryPartnerships, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustryPartnerships Context triple: [Algonquin College, hasIndustryPartnerships, yes]
-
A.
hasIndustryProgram
Indicates that an entity offers, participates in, or is associated with a structured program involving collaboration or engagement with industry organizations or sectors.
-
B.
hasPartnerOrganization
Indicates that an entity is formally associated or collaborates with another entity as a partner organization.
-
C.
hasPartnershipType
Indicates the specific kind or category of partnership relationship that exists between entities.
-
D.
hasNetworkPartner
Indicates that an entity is connected to another entity through a formal or recognized network partnership relationship.
-
E.
hasPartner
Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with another entity.
- F. None of above. chosen
Provenance (4 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_69a8864a83848190a4ec02721306c511 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb231de14819091da3a20ed03c430 |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafde4598819099d8229128348fd3 |
completed | March 7, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69abb22f36f08190abf5e295ddf310d7 |
completed | March 7, 2026, 5:05 a.m. |
Created at: March 4, 2026, 7:33 p.m.