Triple
T23628806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ETA |
E583548
|
entity |
| Predicate | estimatedFatalitiesCaused |
P700
|
FINISHED |
| Object | over 800 people |
—
|
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: over 800 people | Statement: [ETA, estimatedFatalitiesCaused, over 800 people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedFatalitiesCaused Context triple: [ETA, estimatedFatalitiesCaused, over 800 people]
-
A.
causedFatalities
Indicates that the referenced event or action directly resulted in one or more deaths.
-
B.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
C.
indirectFatalitiesCause
Indicates a causal relationship where an entity is responsible for deaths that occur indirectly, as a secondary or downstream consequence rather than as the immediate cause.
-
D.
deathTollEstimate
chosen
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
E.
fatalitiesLocation
Indicates the place where deaths or fatal incidents occurred.
- 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_69e248fc8d74819091bd5baef2f36f6f |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b1e5ae80819085c417e8d81b74ad |
completed | April 29, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:46 p.m.