Triple
T11771476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinchon Campus |
E279907
|
entity |
| Predicate | hasStudentPopulationCharacteristic |
P21454
|
FINISHED |
| Object | large student population |
—
|
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: large student population | Statement: [Sinchon Campus, hasStudentPopulationCharacteristic, large student population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentPopulationCharacteristic Context triple: [Sinchon Campus, hasStudentPopulationCharacteristic, large student population]
-
A.
servesStudentPopulation
Indicates that an entity provides services, resources, or support to a defined group of students.
-
B.
studentPopulationLevel
chosen
Indicates the relative size or magnitude of the student population associated with an entity.
-
C.
universityCharacteristic
Indicates that a specified characteristic, quality, or attribute is associated with a particular university.
-
D.
primaryStudentPopulation
Indicates the number or group of students who are enrolled at the primary or elementary level within an educational institution or system.
-
E.
hasDiverseStudentBody
Indicates that an educational institution’s student population includes a wide range of backgrounds, characteristics, or identities.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a8c2e8b08190a31b1e284fca2aee |
completed | April 10, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69d8a242cd8c819086ed6c5f292dc8cb |
completed | April 10, 2026, 7:09 a.m. |
Created at: April 8, 2026, 9:41 p.m.