Triple
T31082641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Fada |
E792141
|
entity |
| Predicate | casualtiesChadianKilled |
P172947
|
FINISHED |
| Object | approximately 18 |
—
|
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 18 | Statement: [Battle of Fada, casualtiesChadianKilled, approximately 18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesChadianKilled Context triple: [Battle of Fada, casualtiesChadianKilled, approximately 18]
-
A.
casualtiesMahdistSide
Indicates the number of people killed, wounded, or otherwise harmed on the Mahdist side in a conflict or violent event.
-
B.
casualtiesCiviliansKilled
Indicates that the relationship records the number of civilian deaths resulting from a specific event or action.
-
C.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
D.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
E.
casualtiesJordan
Indicates that an event or action resulted in casualties (deaths or injuries) among people in Jordan.
- 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_69f224ce48348190bd0fc23f656ed683 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6b2d9aad88190a445f8f591cb19fc |
completed | May 3, 2026, 2:28 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: April 29, 2026, 9:02 p.m.