Triple
T1956642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SA |
E42283
|
entity |
| Predicate | usedInShipping |
P25490
|
FINISHED |
| Object | country identification in maritime databases |
—
|
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: country identification in maritime databases | Statement: [SA, usedInShipping, country identification in maritime databases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInShipping Context triple: [SA, usedInShipping, country identification in maritime databases]
-
A.
hasShip
Indicates that one entity possesses, owns, or is equipped with a ship.
-
B.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
-
C.
usedInInternationalTrade
Indicates that something participates as a good, service, or instrument in commercial exchanges between different countries.
-
D.
areUsedIn
chosen
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
E.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb68a8e608190bc37a85913b3cd44 |
completed | March 7, 2026, 5:24 a.m. |
| PD | Predicate disambiguation | batch_69abaff5dbd48190a9d36ca60de151db |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.