Triple
T8615127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khasi Hills |
E204015
|
entity |
| Predicate | rainfallCharacteristic |
P17982
|
FINISHED |
| Object | among the wettest regions in the world |
—
|
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: among the wettest regions in the world | Statement: [Khasi Hills, rainfallCharacteristic, among the wettest regions in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rainfallCharacteristic Context triple: [Khasi Hills, rainfallCharacteristic, among the wettest regions in the world]
-
A.
hasExtremeWeatherCharacteristic
chosen
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
B.
hydrologicalCharacteristic
Indicates a relationship where a hydrological feature or condition (such as water flow, level, or behavior) characterizes or describes another entity.
-
C.
rainfallImpact
Indicates how rainfall influences or alters the condition, behavior, or outcome of a target entity or process.
-
D.
rainfallPeak
Indicates the time or value at which rainfall intensity reaches its maximum during a given period or event.
-
E.
primaryRainfallSource
Indicates that one entity is the main origin or contributing source of rainfall for another entity or region.
- 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_69ca832ceab8819096e4a9f546695079 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc47020748819090f658c115c1a7b9 |
completed | March 31, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cc455437488190b7506f820daf6e32 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:25 p.m.