Triple
T521974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Air Force Academy |
E10835
|
entity |
| Predicate | offersMajorField |
P2582
|
FINISHED |
| Object | engineering |
—
|
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: engineering | Statement: [United States Air Force Academy, offersMajorField, engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersMajorField Context triple: [United States Air Force Academy, offersMajorField, engineering]
-
A.
offersFieldOfStudy
chosen
Indicates that an institution or program provides a particular field of study as an available area of academic focus.
-
B.
offersDegree
Indicates that an institution or program provides a specific academic degree as an available qualification.
-
C.
offersDiscipline
Indicates that one entity provides or makes available a particular field of study, training, or area of specialization to another entity.
-
D.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
E.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1b372408190b3918fec45444674 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f018129c81909494450fcba71b59 |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.