Triple
T36415595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Oglethorpe (AKA-100) |
E896992
|
entity |
| Predicate | shipRoleClass |
P185470
|
FINISHED |
| Object | attack cargo |
—
|
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: attack cargo | Statement: [USS Oglethorpe (AKA-100), shipRoleClass, attack cargo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipRoleClass Context triple: [USS Oglethorpe (AKA-100), shipRoleClass, attack cargo]
-
A.
shipClass
Indicates the classification or type category to which a particular ship belongs.
-
B.
fleetOrClass
Indicates that something belongs to, is part of, or is categorized under a particular fleet or class.
-
C.
submarineClassRole
Indicates the functional role or mission type assigned to a particular class of submarines within a naval context.
-
D.
shipNumberInClass
Indicates the specific ordinal position or sequence number that a ship holds within its class.
-
E.
IMOCategory
Indicates the classification of an entity according to the International Mathematical Olympiad (IMO) category it belongs to.
- 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_69f76e54ce408190849acc3f7758937c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.