Triple
T17683838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Miguel campus |
E440836
|
entity |
| Predicate | hasStudentPopulationRegion |
P9355
|
FINISHED |
| Object | eastern departments of El Salvador |
—
|
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: eastern departments of El Salvador | Statement: [San Miguel campus, hasStudentPopulationRegion, eastern departments of El Salvador]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentPopulationRegion Context triple: [San Miguel campus, hasStudentPopulationRegion, eastern departments of El Salvador]
-
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.
hasServiceAreaPopulation
Indicates that an entity has a service area characterized by a specific population size or count.
-
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.
hasRegionalSchool
Indicates that an entity has an associated school that serves or operates within a specific geographic region.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4704626308190bbdd98d27beb3f24 |
completed | April 19, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69e3cde3673c8190a889e14ba1f07dc1 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10:02 a.m.