Triple
T7446620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samoa Islands archipelago |
E171898
|
entity |
| Predicate | hasTropicalCyclones |
P76970
|
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: [Samoa Islands archipelago, hasTropicalCyclones, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTropicalCyclones Context triple: [Samoa Islands archipelago, hasTropicalCyclones, yes]
-
A.
isTropicalCycloneBasin
Indicates that a given geographic region or body of water functions as a basin where tropical cyclones can form or occur.
-
B.
numberOfTropicalDepressions
Indicates the count of tropical depressions associated with or occurring in relation to a given entity or context.
-
C.
numberOfHurricanes
Indicates the total count of hurricanes associated with a specified context, such as a region, time period, or event.
-
D.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
E.
numberOfNamedStorms
Indicates the total count of distinct storms that have been formally assigned names within a specified context or period.
- 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_69c68a65402881908f7869368eb746fb |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f371be2081908feaeb9392cb65fe |
completed | March 27, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69c6f039f7248190bb4183f97b605763 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1ee5ab8819091082324f2dc3b8c |
completed | March 27, 2026, 9:09 p.m. |
Created at: March 27, 2026, 3:14 p.m.