Triple
T10509712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American University of Paris |
E247879
|
entity |
| Predicate | percentageInternationalStudents |
P4356
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [American University of Paris, percentageInternationalStudents, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageInternationalStudents Context triple: [American University of Paris, percentageInternationalStudents, high]
-
A.
internationalStudentsShare
chosen
Indicates the proportion or percentage of a population or group that consists of international students.
-
B.
hasInternationalStudents
Indicates that an institution or organization includes students who come from countries other than the one in which it is located.
-
C.
internationalProgram
Indicates a program that involves participation, collaboration, or exchange across multiple countries or international boundaries.
-
D.
internationalCampusLocation
Indicates that an educational institution has a campus located in a country different from its primary or home country.
-
E.
immigrantPopulationShare
Indicates the proportion of a total population that is made up of immigrants.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509b359ac8190b3683cc6b9c70a71 |
completed | April 7, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:27 p.m.