Triple
T33950749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khodynka Tragedy |
E870432
|
entity |
| Predicate | hasDeathToll |
P700
|
FINISHED |
| Object | approximately 1300 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: approximately 1300 people | Statement: [Khodynka Tragedy, hasDeathToll, approximately 1300 people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDeathToll Context triple: [Khodynka Tragedy, hasDeathToll, approximately 1300 people]
-
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.
notableDeathTollEvent
Indicates that an event is characterized by causing an unusually large or historically significant number of 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.
causedFatalities
Indicates that the referenced event or action directly resulted in one or more 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_69f3499c2d7481909c953a5010227725 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fefb15220081908da36aac386fa582 |
completed | May 9, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69fefa8e8ad48190a723fed81e9d64d0 |
completed | May 9, 2026, 9:12 a.m. |
Created at: May 1, 2026, 1:49 a.m.