Triple
T2033516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Möhne Dam |
E44569
|
entity |
| Predicate | casualtiesAssociatedWithEvent |
P35438
|
FINISHED |
| Object | over 1,000 people killed in 1943 flood |
—
|
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: over 1,000 people killed in 1943 flood | Statement: [Möhne Dam, casualtiesAssociatedWithEvent, over 1,000 people killed in 1943 flood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesAssociatedWithEvent Context triple: [Möhne Dam, casualtiesAssociatedWithEvent, over 1,000 people killed in 1943 flood]
-
A.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
B.
casualtiesDescription
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
C.
casualtiesIncluded
Indicates that the referenced count or report of casualties explicitly includes the specified individuals or groups.
-
D.
casualtiesImpact
Indicates how the number or severity of casualties affects or influences another factor, situation, or outcome.
-
E.
casualtiesType
Indicates the specific category or nature of casualties (e.g., killed, injured, missing) associated with an event or incident.
- 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_69a889144f2481909932f0746a93023d |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb93255248190bd47a54a7b3c7447 |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb7a8125881909c0cb58b777c1faa |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb90ec7948190bbfb0329e9e67cca |
completed | March 7, 2026, 5:35 a.m. |
Created at: March 4, 2026, 7:39 p.m.