Triple
T484422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marist College |
E9842
|
entity |
| Predicate | hasStudyAbroad |
P13515
|
FINISHED |
| Object | programs in multiple countries |
—
|
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: programs in multiple countries | Statement: [Marist College, hasStudyAbroad, programs in multiple countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudyAbroad Context triple: [Marist College, hasStudyAbroad, programs in multiple countries]
-
A.
hasLanguageOfStudy
Indicates that an entity studies or is engaged in learning a particular language.
-
B.
isStudiedIn
Indicates that a subject (such as a topic, field, or phenomenon) is examined, researched, or learned about within a particular context, environment, or discipline.
-
C.
internationalStudentsShare
Indicates the proportion or percentage of a population or group that consists of international students.
-
D.
studiedUnder
Indicates that one entity received instruction, training, or mentorship from another, typically in an academic or apprenticeship context.
-
E.
offersFieldOfStudy
Indicates that an institution or program provides a particular field of study as an available area of academic focus.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0ba310c81909645ef7e8a20b52f |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf48ec08190b85d07e194f99c49 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeba8a488190986cc7381332f783 |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.