Triple
T3060326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nazi occupation of the Netherlands |
E60580
|
entity |
| Predicate | casualtiesOfBombingOfRotterdam |
P34639
|
FINISHED |
| Object | approximately 800 to 900 civilians killed |
—
|
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 to 900 civilians killed | Statement: [Nazi occupation of the Netherlands, casualtiesOfBombingOfRotterdam, approximately 800 to 900 civilians killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesOfBombingOfRotterdam Context triple: [Nazi occupation of the Netherlands, casualtiesOfBombingOfRotterdam, approximately 800 to 900 civilians killed]
-
A.
dutchCasualties
chosen
Indicates that the relationship specifies the number or occurrence of casualties suffered by Dutch entities in a given event or context.
-
B.
cityBombed
Indicates that a particular city was subjected to a bombing attack.
-
C.
wasBombedOn
Indicates that a location or target experienced a bombing event at a specific time or date.
-
D.
mainCityDestroyed
Indicates that the primary or central city associated with an entity has been destroyed.
-
E.
resultOfBombing
Indicates that something exists or occurs as a consequence or outcome of a bombing event.
- 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.