Triple
T23225000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2013 North India floods |
E580989
|
entity |
| Predicate | deathTollOfficialUttarakhand |
P700
|
FINISHED |
| Object | around 5,700 people presumed dead |
—
|
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: around 5,700 people presumed dead | Statement: [2013 North India floods, deathTollOfficialUttarakhand, around 5,700 people presumed dead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathTollOfficialUttarakhand Context triple: [2013 North India floods, deathTollOfficialUttarakhand, around 5,700 people presumed dead]
-
A.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
B.
deathTollEstimate
chosen
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
C.
causedFatalities
Indicates that the referenced event or action directly resulted in one or more deaths.
-
D.
deathTollRanking
Indicates the relative position of an event or entity when ordered by the number of deaths it caused, typically from highest to lowest.
-
E.
notableDeathTollEvent
Indicates that an event is characterized by causing an unusually large or historically significant number of deaths.
- 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_69e246043c48819089bae72c9a9c306c |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f1922d30b08190a3c54bab58f5c8e7 |
completed | April 29, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69effcccee508190a7ae311fdd319806 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:08 p.m.