Triple
T16349285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naval Hospital Beaufort |
E397014
|
entity |
| Predicate | isMilitaryTreatmentFacility |
P123073
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Naval Hospital Beaufort, isMilitaryTreatmentFacility, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMilitaryTreatmentFacility Context triple: [Naval Hospital Beaufort, isMilitaryTreatmentFacility, true]
-
A.
isMilitaryInstallation
Indicates that a location functions as a military facility or base used for defense, training, operations, or related armed forces activities.
-
B.
isMilitaryPostType
Indicates that something is classified as a type or category of military post or installation.
-
C.
isAcuteCareFacility
Indicates that the entity functions as a healthcare facility providing short-term, intensive medical treatment for patients with severe or urgent conditions.
-
D.
locatedOnMilitaryInstallation
Indicates that one entity is physically situated within the boundaries of, or directly on, a military installation or base.
-
E.
isTeachingHospitalFor
Indicates that one institution serves as a clinical training site or educational facility for another, typically a medical school or health education program.
- F. None of above. chosen
Provenance (4 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2da120ec081909bbf32bd128b2e01 |
completed | April 18, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:07 a.m.