Triple
T3605870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanport Extension Center |
E76368
|
entity |
| Predicate | studentPopulationCharacteristic |
P299
|
FINISHED |
| Object | many students were military veterans |
—
|
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: many students were military veterans | Statement: [Vanport Extension Center, studentPopulationCharacteristic, many students were military veterans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentPopulationCharacteristic Context triple: [Vanport Extension Center, studentPopulationCharacteristic, many students were military veterans]
-
A.
studentPopulationLevel
Indicates the relative size or magnitude of the student population associated with an entity.
-
B.
servesStudentPopulation
Indicates that an entity provides services, resources, or support to a defined group of students.
-
C.
demographicsCharacteristic
chosen
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
-
D.
populationClass
Indicates a categorical classification of a population based on shared characteristics, status, or demographic criteria.
-
E.
universityCharacteristic
Indicates that a specified characteristic, quality, or attribute is associated with a particular university.
- 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_69ad85d93dcc819094fba90cf70f4996 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc1e1f9188190b481c26b7f561db7 |
completed | March 8, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69adb83d8b1c8190b3bddbc5dc995a87 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:22 p.m.