Triple
T18747077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yemeni Civil War |
E458431
|
entity |
| Predicate | hasChildCasualties |
P133394
|
FINISHED |
| Object | tens of thousands of children |
—
|
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: tens of thousands of children | Statement: [Yemeni Civil War, hasChildCasualties, tens of thousands of children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChildCasualties Context triple: [Yemeni Civil War, hasChildCasualties, tens of thousands of children]
-
A.
hasCasualtiesLevel
Indicates the severity or extent of casualties associated with an event, incident, or situation.
-
B.
casualtiesIncluded
Indicates that the referenced count or report of casualties explicitly includes the specified individuals or groups.
-
C.
primaryCasualtiesFrom
Indicates that an entity is the main source or cause of the casualties experienced by another entity.
-
D.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
E.
casualtiesHuman
Indicates a relationship where a human entity suffers harm, injury, or death as a result of an event, action, or situation.
- 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e576936cf08190b3c0d2f4e8a616fc |
completed | April 20, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:51 a.m.