Triple
T24418754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VN |
E615665
|
entity |
| Predicate | usedInInternationalStatistics |
P42991
|
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: [VN, usedInInternationalStatistics, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInInternationalStatistics Context triple: [VN, usedInInternationalStatistics, yes]
-
A.
usedInUNStatistics
chosen
Indicates that something is employed or referenced within official United Nations statistical data, classifications, or reporting.
-
B.
usedInStatistic
Indicates that something (such as a value, measure, or data item) is employed as part of the calculation or presentation of a particular statistic.
-
C.
usedInInternationalTrade
Indicates that something participates as a good, service, or instrument in commercial exchanges between different countries.
-
D.
usedByOtherCountries
Indicates that something (such as a method, resource, or technology) is utilized or adopted by countries other than the one primarily associated with it.
-
E.
usedByCountriesWith
Indicates that something (such as an item, system, or practice) is utilized or employed by one or more specified countries in common.
- 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_69e2d7e9bfac8190a748952a90957106 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296a12a50819099fcdbc7096b53dd |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:13 a.m.