Triple
T16421726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crossbarry Ambush |
E398833
|
entity |
| Predicate | casualtiesIRA |
P10775
|
FINISHED |
| Object | several 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: several killed | Statement: [Crossbarry Ambush, casualtiesIRA, several killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesIRA Context triple: [Crossbarry Ambush, casualtiesIRA, several killed]
-
A.
casualtiesIraqiMilitaryKilled
Indicates that the number of casualties refers specifically to Iraqi military personnel who were killed.
-
B.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
C.
casualtiesIraqiEquipment
Indicates that Iraqi equipment has suffered damage, destruction, or loss as a result of a particular event or action.
-
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.
sustainedHeavyCasualtiesAt
Indicates that an entity experienced a large number of serious losses (e.g., deaths or injuries) at a specific location or during a specific event.
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328f85a68819098742b324f6c6fd4 |
completed | April 18, 2026, 6:47 a.m. |
| PD | Predicate disambiguation | batch_69e22701d2288190bf8676050758f172 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:09 a.m.