Triple
T9407614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Montserrat |
E226625
|
entity |
| Predicate | seaUse |
P4959
|
FINISHED |
| Object | government vessels |
—
|
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: government vessels | Statement: [Flag of Montserrat, seaUse, government vessels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seaUse Context triple: [Flag of Montserrat, seaUse, government vessels]
-
A.
maritimeUsage
Indicates the extent to which something is used for or involved in maritime activities, such as sea transport, navigation, or ocean-related operations.
-
B.
usesAtSea
chosen
Indicates that something is employed, operated, or applied in a maritime or oceanic environment.
-
C.
marineArea
Indicates a relationship where an entity is located in, associated with, or relevant to a specific marine or oceanic area.
-
D.
maritimeActivity
Indicates activities, operations, or behaviors that take place at sea or are directly related to maritime environments and navigation.
-
E.
seaOf
Indicates a relationship where one entity is metaphorically or literally surrounded or filled by another like a vast sea, emphasizing overwhelming abundance or expansiveness.
- 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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5252b3fc8190b0808a10987728c8 |
completed | April 1, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:47 p.m.