Triple
T2558596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Benburb |
E56786
|
entity |
| Predicate | casualtiesSide1 |
P10775
|
FINISHED |
| Object | light Irish Confederate casualties |
—
|
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: light Irish Confederate casualties | Statement: [Battle of Benburb, casualtiesSide1, light Irish Confederate casualties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesSide1 Context triple: [Battle of Benburb, casualtiesSide1, light Irish Confederate casualties]
-
A.
coalitionCasualties
Indicates that members of a coalition have suffered deaths or injuries as a result of a particular conflict, event, or action.
-
B.
casualtiesAllied
Indicates the number or extent of losses (killed, wounded, or missing) suffered by allied forces in a conflict or incident.
-
C.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
D.
casualtiesDescription
chosen
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
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.
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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35c6ee88190b6eaa1841d3e99a4 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0caeb488190b0dd8e48d0f2777d |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.