Triple
T38454495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sirajganj Sadar Upazila |
E912270
|
entity |
| Predicate | experiencesWeatherEvent |
P2044
|
FINISHED |
| Object | monsoon flooding |
—
|
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: monsoon flooding | Statement: [Sirajganj Sadar Upazila, experiencesWeatherEvent, monsoon flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: experiencesWeatherEvent Context triple: [Sirajganj Sadar Upazila, experiencesWeatherEvent, monsoon flooding]
-
A.
hasWeather
chosen
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
B.
hasWeatherExposure
Indicates that something is subject to or affected by outdoor weather conditions or elements.
-
C.
allWeatherCapability
Indicates that an entity is capable of operating effectively under all weather conditions.
-
D.
hasWeatherContext
Indicates that something is associated with, influenced by, or described in terms of specific weather conditions or patterns.
-
E.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
- 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_69f76e84e2dc81908badf05b3aafa9ea |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcce7afcd08190906cc3801152656a |
completed | May 7, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69fcccf140ec8190862d53388a5f40d7 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:31 p.m.