Triple
T16835228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 9M-MRD |
E409256
|
entity |
| Predicate | passengersAtTimeOfDestruction |
P125029
|
FINISHED |
| Object | 283 |
—
|
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: 283 | Statement: [9M-MRD, passengersAtTimeOfDestruction, 283]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengersAtTimeOfDestruction Context triple: [9M-MRD, passengersAtTimeOfDestruction, 283]
-
A.
fatalitiesOnboard
Indicates that the relationship specifies the number of people who died among those present on a particular vehicle or craft.
-
B.
timeOfDestruction
Indicates the specific time at which an entity is destroyed or ceases to exist.
-
C.
honorsNumberOfPassengersAndCrew
Indicates that the subject recognizes or commemorates the specified count of passengers and crew.
-
D.
yearOfDestruction
Indicates the specific year in which an entity was destroyed or ceased to exist.
-
E.
survivorsInFinalAccident
Indicates that the referenced entities are those who remained alive after the final accident in a sequence of accidents.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:23 a.m.