Triple
T7685652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Folke Bernadotte |
E174108
|
entity |
| Predicate | rescuedPrisonersNumberApprox |
P8803
|
FINISHED |
| Object | 31000 |
—
|
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: 31000 | Statement: [Folke Bernadotte, rescuedPrisonersNumberApprox, 31000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rescuedPrisonersNumberApprox Context triple: [Folke Bernadotte, rescuedPrisonersNumberApprox, 31000]
-
A.
estimatedPrisoners
Indicates a relationship where a value represents the estimated number of prisoners associated with a particular entity or context.
-
B.
estimatedNumberOfSurvivorsAtLiberation
Indicates the approximate count of individuals who were still alive at the time a camp or similar site was liberated.
-
C.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
-
D.
estimatedNumberOfPeopleSaved
chosen
Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or entity.
-
E.
numberOfPrisonersApproximate
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:02 p.m.