Triple
T141289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World War I |
E2855
|
entity |
| Predicate | militaryCasualtiesEstimate |
P6773
|
FINISHED |
| Object | millions of soldiers 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: millions of soldiers killed | Statement: [World War I, militaryCasualtiesEstimate, millions of soldiers killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryCasualtiesEstimate Context triple: [World War I, militaryCasualtiesEstimate, millions of soldiers killed]
-
A.
casualtiesEstimate
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
-
B.
deathTollEstimate
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
C.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
D.
casualtiesKilledUS
Indicates that the relationship specifies the number of U.S. individuals who were killed as casualties in an event or incident.
-
E.
casualtiesUnitedStates
Indicates that the event or situation resulted in casualties (deaths and/or injuries) among United States personnel or citizens.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565559ac81909e0c4e095a7dfa27 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2580b00988190868ee24c0289cf70 |
completed | Feb. 28, 2026, 2:50 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.