Triple
T16835230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 9M-MRD |
E409256
|
entity |
| Predicate | fatalitiesAtTimeOfDestruction |
P1785
|
FINISHED |
| Object | 298 |
—
|
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: 298 | Statement: [9M-MRD, fatalitiesAtTimeOfDestruction, 298]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatalitiesAtTimeOfDestruction Context triple: [9M-MRD, fatalitiesAtTimeOfDestruction, 298]
-
A.
deathToll
chosen
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
B.
demolitionCasualties
Indicates that an act of demolition resulted in injuries or deaths to people involved or nearby.
-
C.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
D.
fatalitiesOnboard
Indicates that the relationship specifies the number of people who died among those present on a particular vehicle or craft.
-
E.
deathTollEstimate
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b31aa44c8190b4f402f1898e6998 |
completed | April 18, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:23 a.m.