Triple
T21197432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Vietnam Navy |
E522361
|
entity |
| Predicate | typeOfVesselsUsed |
P11945
|
FINISHED |
| Object | patrol boats |
—
|
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: patrol boats | Statement: [Republic of Vietnam Navy, typeOfVesselsUsed, patrol boats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfVesselsUsed Context triple: [Republic of Vietnam Navy, typeOfVesselsUsed, patrol boats]
-
A.
vesselTypeServedOn
Indicates the type of vessel on which an entity has served or performed duty.
-
B.
usesVesselType
chosen
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
-
C.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
D.
shipTypeInvolved
Indicates that a particular type or class of ship is involved or participates in a specified event, situation, or relationship.
-
E.
sponsoredVesselType
Indicates that one entity has provided sponsorship or financial backing specifically for a vessel of a given type.
- 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7333c9bac8190a203802a8b8e4143 |
completed | April 21, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:11 p.m.