Triple
T4737304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McGurk's Bar bombing |
E105155
|
entity |
| Predicate | fatalitiesDescription |
P10775
|
FINISHED |
| Object | 15 civilians 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: 15 civilians killed | Statement: [McGurk's Bar bombing, fatalitiesDescription, 15 civilians killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatalitiesDescription Context triple: [McGurk's Bar bombing, fatalitiesDescription, 15 civilians killed]
-
A.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
B.
casualtiesDescription
chosen
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
C.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
D.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
E.
fatalitiesOnboard
Indicates that the relationship specifies the number of people who died among those present on a particular vehicle or craft.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64844b7081909c9d36e4b461379e |
completed | March 20, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69bd6221c3b881908604f35f8de6f16b |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:19 p.m.