Triple
T3060342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nazi occupation of the Netherlands |
E60580
|
entity |
| Predicate | estimatedDeathsHungerWinter |
P700
|
FINISHED |
| Object | approximately 20,000 civilians |
—
|
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 20,000 civilians | Statement: [Nazi occupation of the Netherlands, estimatedDeathsHungerWinter, approximately 20,000 civilians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedDeathsHungerWinter Context triple: [Nazi occupation of the Netherlands, estimatedDeathsHungerWinter, approximately 20,000 civilians]
-
A.
numberOfHoldersKilledInWorldWarII
Indicates the number of holders of a given title, position, or role who were killed during World War II.
-
B.
numberOfGermanVictims
Indicates the quantity of victims who are identified as German in the context of the described event or situation.
-
C.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
D.
deathTollEstimate
chosen
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
E.
numberOfJewsKilled
Indicates the quantity of Jewish people who were killed in a given event, context, or time period.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9e9cf9188190b43f50edc009030d |
completed | March 8, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69ad962326e081909d5521c3d3ea3158 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.