Triple
T29421372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FI |
E746164
|
entity |
| Predicate | usedInInternationalMail |
P190669
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [FI, usedInInternationalMail, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInInternationalMail Context triple: [FI, usedInInternationalMail, yes]
-
A.
usedInInternationalTrade
Indicates that something participates as a good, service, or instrument in commercial exchanges between different countries.
-
B.
isInternational
Indicates that something has a connection to, involves, or extends across more than one country.
-
C.
usesForCommercialShipping
Indicates that something is employed as a means or method for transporting goods in a commercial or business context.
-
D.
usedInConstituentCountry
Indicates that something is utilized or applied within a specific constituent country of a larger sovereign state.
-
E.
usedForCountry
Indicates that something is used for, or serves a purpose related to, a specific country.
- F. None of above. chosen
Provenance (4 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_69f0a79f6d5c8190a350baed0157e06f |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fcce2cf9188190b3f65b362203a6a3 |
completed | May 7, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fccdd2d84481909a7ce22407def9c7 |
completed | May 7, 2026, 5:37 p.m. |
Created at: April 28, 2026, 3:06 p.m.