Triple
T259940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS West Virginia (BB-48) |
E5518
|
entity |
| Predicate | armorBelt |
P10290
|
FINISHED |
| Object | up to 13.5 inches |
—
|
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: up to 13.5 inches | Statement: [USS West Virginia (BB-48), armorBelt, up to 13.5 inches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armorBelt Context triple: [USS West Virginia (BB-48), armorBelt, up to 13.5 inches]
-
A.
armour
Indicates that an entity provides protective covering or defense for another entity.
-
B.
typicalWeapon
Indicates that the object is a weapon commonly or characteristically used by the subject.
-
C.
authorizedHeadgear
Indicates that a particular item of headgear is officially permitted or approved for use in a given context or by a specific authority.
-
D.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
E.
hasBowType
Indicates that an entity possesses or is associated with a specific type or category of bow.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25f921c2881908821ca2c03815eae |
completed | Feb. 28, 2026, 3:22 a.m. |
| PD | Predicate disambiguation | batch_69a25b6b3ea88190bbd858999e42efae |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25f9163f881909232f8aea502cf80 |
completed | Feb. 28, 2026, 3:22 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.