Triple
T9369339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Entebbe |
E225488
|
entity |
| Predicate | casualtiesUgandanSoldiers |
P88178
|
FINISHED |
| Object | dozens 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: dozens killed | Statement: [Operation Entebbe, casualtiesUgandanSoldiers, dozens killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesUgandanSoldiers Context triple: [Operation Entebbe, casualtiesUgandanSoldiers, dozens killed]
-
A.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
B.
casualtiesUKKilled
Indicates that the relationship specifies the number of people from the UK who were killed in the referenced event or incident.
-
C.
casualtiesDescription
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
D.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
E.
casualtiesUnion
Indicates a relationship where multiple casualty figures or reports are combined into a single aggregated total.
- 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_69ca842cbddc819099d71ecec48cf9e5 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5080f55c8190bd5ca0dc0a4ea989 |
completed | April 1, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69cc7a6abb8c81908c7a2f4ee92cc949 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:43 p.m.