Triple
T748337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Kitts and Nevis |
E15391
|
entity |
| Predicate | areaRankInWesternHemisphere |
P1170
|
FINISHED |
| Object | smallest sovereign state by area |
—
|
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: smallest sovereign state by area | Statement: [Saint Kitts and Nevis, areaRankInWesternHemisphere, smallest sovereign state by area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaRankInWesternHemisphere Context triple: [Saint Kitts and Nevis, areaRankInWesternHemisphere, smallest sovereign state by area]
-
A.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
B.
continentRankByPopulation
Indicates the relative position of a continent in an ordered list based on its population size.
-
C.
continentRankByArea
Indicates the relative position of a continent in an ordered list based on its total land area.
-
D.
areaRankInUS
Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
-
E.
areaRank
chosen
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
- 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62f31888190b80cb0a7220f8d80 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a5004f708190a984ee221716e19c |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.