Triple
T521978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Air Force Academy |
E10835
|
entity |
| Predicate | hasCampusArea |
P53
|
FINISHED |
| Object | approximately 18,000 acres |
—
|
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: approximately 18,000 acres | Statement: [United States Air Force Academy, hasCampusArea, approximately 18,000 acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampusArea Context triple: [United States Air Force Academy, hasCampusArea, approximately 18,000 acres]
-
A.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
B.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
-
C.
hasAdditionalCampus
Indicates that an educational institution maintains one or more campuses in addition to its primary or main campus.
-
D.
hasMainCampus
Indicates that an educational institution is primarily based at or chiefly associated with a particular campus location.
-
E.
campusSize
chosen
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
- 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.