Triple
T11366971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glasnevin Campus |
E269232
|
entity |
| Predicate | hasStudentPopulationScope |
P9355
|
FINISHED |
| Object | majority of DCU students |
—
|
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: majority of DCU students | Statement: [Glasnevin Campus, hasStudentPopulationScope, majority of DCU students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentPopulationScope Context triple: [Glasnevin Campus, hasStudentPopulationScope, majority of DCU students]
-
A.
servesStudentPopulation
chosen
Indicates that an entity provides services, resources, or support to a defined group of students.
-
B.
studentPopulationLevel
Indicates the relative size or magnitude of the student population associated with an entity.
-
C.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
D.
hasNumberOfSchools
Indicates the quantity of schools associated with a given entity.
-
E.
primaryStudentPopulation
Indicates the number or group of students who are enrolled at the primary or elementary level within an educational institution or system.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e7022d508190996f9be0847c2b41 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.