Triple
T22538707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrée de Jongh |
E557225
|
entity |
| Predicate | estimatedAirmenHelped |
P148585
|
FINISHED |
| Object | approximately 800 |
—
|
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 800 | Statement: [Andrée de Jongh, estimatedAirmenHelped, approximately 800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedAirmenHelped Context triple: [Andrée de Jongh, estimatedAirmenHelped, approximately 800]
-
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.
estimatedAerialVictories
Indicates an approximate count of aerial combat victories attributed to an entity, rather than an exact, confirmed total.
-
C.
approximateNumberOfRefugeesTransported
Indicates an estimated count of refugees who were transported in the described event or context.
-
D.
numberOfTroopsEvacuated
Indicates the quantity of troops that have been removed from a location or situation and transported to safety.
-
E.
numberOfRescuers
Indicates the quantity of rescuers involved in or assigned to a particular rescue-related situation or event.
- 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f302cd4819098c97ca4fa96363e |
completed | April 29, 2026, 1:30 a.m. |
| PD | Predicate disambiguation | batch_69e898c864148190a3f5feec7967d49c |
completed | April 22, 2026, 9:45 a.m. |
| PDg | Predicate description generation | batch_69e8aa3b4c288190951cca06d42bea51 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:51 p.m.