Triple
T10473253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wieluń |
E246981
|
entity |
| Predicate | bombardmentCivilianCasualties |
P34802
|
FINISHED |
| Object | hundreds of 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: hundreds of civilians killed | Statement: [Wieluń, bombardmentCivilianCasualties, hundreds of civilians killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bombardmentCivilianCasualties Context triple: [Wieluń, bombardmentCivilianCasualties, hundreds of civilians killed]
-
A.
wasBombedDuring
Indicates that an entity was subjected to a bombing attack during a specified event or time period.
-
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.
wasBombardedDuring
Indicates that an entity was subjected to a bombardment (e.g., shelling, bombing, or heavy attack) during a specified event or time period.
-
E.
casualtiesCiviliansKilled
chosen
Indicates that the relationship records the number of civilian deaths resulting from a specific event or action.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5094daac081908e0ba5e10c1bbb67 |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:20 p.m.