Triple
T31130047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treblinka uprising |
E793475
|
entity |
| Predicate | estimatedNumberOfSurvivors |
P176761
|
FINISHED |
| Object | around 70 |
—
|
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: around 70 | Statement: [Treblinka uprising, estimatedNumberOfSurvivors, around 70]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfSurvivors Context triple: [Treblinka uprising, estimatedNumberOfSurvivors, around 70]
-
A.
estimatedNumberOfPeopleSaved
Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or entity.
-
B.
numberOfChildrenSurvivors
Indicates the count of children who survived a particular event, condition, or situation.
-
C.
numberOfSurvivingSpecimens
Indicates the count of individual specimens that remain alive or intact after a particular event, period, or condition.
-
D.
hasSurvivors
Indicates that one or more entities continue to exist or remain alive after a particular event, condition, or incident.
-
E.
hasApproximateNumberOfVictims
Indicates that an entity is associated with an estimated, non-exact count of victims.
- 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_69f224d1701c819094f429798290e361 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69f6e60109648190947a64ca4ce81a3a |
completed | May 3, 2026, 6:06 a.m. |
Created at: April 29, 2026, 9:05 p.m.