Triple
T36679730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2021 European floods |
E905644
|
entity |
| Predicate | deathTollInCountry |
P1785
|
FINISHED |
| Object | Germany: over 180 deaths |
—
|
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: Germany: over 180 deaths | Statement: [2021 European floods, deathTollInCountry, Germany: over 180 deaths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathTollInCountry Context triple: [2021 European floods, deathTollInCountry, Germany: over 180 deaths]
-
A.
deathTollEstimate
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
B.
deathTollRanking
Indicates the relative position of an event or entity when ordered by the number of deaths it caused, typically from highest to lowest.
-
C.
deathToll
chosen
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
D.
casualtiesCountry
Indicates that the specified country is the one in which the recorded casualties (deaths or injuries) occurred or to which those casualties belong.
-
E.
militaryDeaths
Indicates the number of individuals who died while serving in a military capacity, typically during armed conflict or related operations.
- 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_69f76e7011dc819082b324f18b756a1b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:12 p.m.