Triple
T13522357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Engineering and Applied Science |
E322928
|
entity |
| Predicate | offersResearchOpportunitiesIn |
P42231
|
FINISHED |
| Object | engineering |
—
|
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: engineering | Statement: [College of Engineering and Applied Science, offersResearchOpportunitiesIn, engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersResearchOpportunitiesIn Context triple: [College of Engineering and Applied Science, offersResearchOpportunitiesIn, engineering]
-
A.
offersEducationIn
chosen
Indicates that an entity provides or delivers educational programs, courses, or instruction in a specified field, subject, or area.
-
B.
offersEducationTo
Indicates that one entity provides educational services, instruction, or learning opportunities to another entity.
-
C.
offersStudyAbroad
Indicates that an institution or program provides opportunities for participants to study in a foreign country.
-
D.
offersFieldOfStudy
Indicates that an institution or program provides a particular field of study as an available area of academic focus.
-
E.
offersApprenticeshipTraining
Indicates that one entity provides apprenticeship-based training opportunities or programs 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa535cc81908d0018fef81a2848 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:44 p.m.