Triple
T2242836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wentworth Institute of Technology |
E49434
|
entity |
| Predicate | cooperativeEducation |
P30072
|
FINISHED |
| Object | required for many programs |
—
|
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: required for many programs | Statement: [Wentworth Institute of Technology, cooperativeEducation, required for many programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cooperativeEducation Context triple: [Wentworth Institute of Technology, cooperativeEducation, required for many programs]
-
A.
offersApprenticeshipTraining
Indicates that one entity provides apprenticeship-based training opportunities or programs to another entity.
-
B.
businessSchool
Indicates that one entity is a business school attended by, affiliated with, or otherwise educationally related to the other entity.
-
C.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
D.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
E.
offersEducationTo
chosen
Indicates that one entity provides educational services, instruction, or learning opportunities to 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0c017548190a71fb4a0e2a8189f |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.