Triple
T16170890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banryū |
E392430
|
entity |
| Predicate | vesselTypeContext |
P11978
|
FINISHED |
| Object | Bakumatsu-era steam warship |
—
|
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: Bakumatsu-era steam warship | Statement: [Banryū, vesselTypeContext, Bakumatsu-era steam warship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vesselTypeContext Context triple: [Banryū, vesselTypeContext, Bakumatsu-era steam warship]
-
A.
hasVesselType
chosen
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
B.
usesVesselType
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
-
C.
vesselTypeServedOn
Indicates the type of vessel on which an entity has served or performed duty.
-
D.
vesselService
Indicates a service relationship in which one entity provides, operates, or maintains a vessel (such as a ship or boat) for another entity.
-
E.
hasVessel
Indicates that one entity possesses, uses, or is associated with a particular vessel (such as a container, ship, or transport medium) in the context of the described relationship or action.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb6de30819083af54b50ae5ae51 |
completed | April 17, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.