Triple
T87365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Purge |
E1755
|
entity |
| Predicate | estimatedVictims |
P700
|
FINISHED |
| Object | hundreds of thousands executed |
—
|
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: hundreds of thousands executed | Statement: [Great Purge, estimatedVictims, hundreds of thousands executed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedVictims Context triple: [Great Purge, estimatedVictims, hundreds of thousands executed]
-
A.
casualtiesEstimate
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
-
B.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
-
C.
victimGroup
Indicates that one group or entity is the target or recipient of harm, abuse, or wrongdoing caused by another.
-
D.
deathTollEstimate
chosen
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
E.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2503d304c8190a0034ffa4a38a501 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb6da2c8190a33d144d219f7abe |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.