Triple
T10084128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelantan River |
E215175
|
entity |
| Predicate | floodSeasonMonths |
P13044
|
FINISHED |
| Object | November to January |
—
|
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: November to January | Statement: [Kelantan River, floodSeasonMonths, November to January]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floodSeasonMonths Context triple: [Kelantan River, floodSeasonMonths, November to January]
-
A.
seasonalFlow
Indicates that the flow or intensity of something varies in a recurring pattern according to the seasons.
-
B.
floodSeasonCause
Indicates the cause or contributing factor responsible for a particular flood season occurring.
-
C.
hasSeasonalFlooding
chosen
Indicates that an area regularly experiences flooding during specific, recurring times of the year.
-
D.
runoffMonth
Indicates the month during which runoff (such as water flow from precipitation or melting) predominantly occurs or is measured for a given entity.
-
E.
wettestMonths
Indicates the months during which a location experiences the highest amount of precipitation compared to other months.
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd044c1ec8190b5b48cdb0584d00c |
completed | April 2, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9 p.m.