Triple
T30851862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gridley-class destroyer |
E785802
|
entity |
| Predicate | gunArmamentType |
P6073
|
FINISHED |
| Object | 5-inch guns |
—
|
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: 5-inch guns | Statement: [Gridley-class destroyer, gunArmamentType, 5-inch guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gunArmamentType Context triple: [Gridley-class destroyer, gunArmamentType, 5-inch guns]
-
A.
gunType
chosen
Indicates the specific category or kind of gun associated with an entity.
-
B.
weaponsBay
Indicates that one entity serves as the weapons bay (storage or housing area for weapons) of another entity.
-
C.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
-
D.
armedVariants
Indicates that one entity is a version or model of another that is equipped with weapons or enhanced armaments.
-
E.
weaponCategory
Indicates the classification or type of weapon to which an item or armament belongs.
- 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6917d9a908190b43d8ce6b17eb8ac |
completed | May 3, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:46 p.m.