Triple
T259932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS West Virginia (BB-48) |
E5518
|
entity |
| Predicate | fullLoadDisplacement |
P6546
|
FINISHED |
| Object | 33000+ long tons |
—
|
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: 33000+ long tons | Statement: [USS West Virginia (BB-48), fullLoadDisplacement, 33000+ long tons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fullLoadDisplacement Context triple: [USS West Virginia (BB-48), fullLoadDisplacement, 33000+ long tons]
-
A.
displacementFullLoad
chosen
Indicates the total volume of water displaced by a vessel when it is fully loaded to its maximum operational capacity.
-
B.
availableEngineDisplacement
Indicates the range or specific values of engine displacement that are offered or applicable for a given entity.
-
C.
trunkVolume
Indicates the volume or capacity of an entity’s trunk or main storage compartment.
-
D.
enginePower
Indicates the power output produced by an engine, typically quantifying its capability to perform work or generate mechanical energy.
-
E.
hasRefuellingCapabilityFor
Indicates that one entity is capable of providing or performing refuelling operations for another entity.
- 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_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. |
Created at: Feb. 28, 2026, 2:55 a.m.