Triple
T3842594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Texas at El Paso |
E93486
|
entity |
| Predicate | servesPredominantly |
P17274
|
FINISHED |
| Object | Hispanic 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: Hispanic student population | Statement: [University of Texas at El Paso, servesPredominantly, Hispanic student population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesPredominantly Context triple: [University of Texas at El Paso, servesPredominantly, Hispanic student population]
-
A.
servesMostly
chosen
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
B.
typicallyServedAs
Indicates that something is most commonly presented, used, or offered in a particular role, form, or function.
-
C.
primaryServes
Indicates that one entity’s main or principal function is to serve, support, or provide service to another entity.
-
D.
intendedToServe
Indicates that one entity was designed, planned, or purposed specifically to benefit, assist, or fulfill the needs of another entity.
-
E.
servesType
Indicates that one entity provides, offers, or is used to deliver a particular type, category, or kind of thing or service.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb397ac81908f74a42a0eeb8682 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee74dcecc819098285483ec721b40 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.