Triple
T4847157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McNamara brothers bombing case |
E108317
|
entity |
| Predicate | hasVictims |
P59760
|
FINISHED |
| Object | people killed in bombing |
—
|
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: people killed in bombing | Statement: [McNamara brothers bombing case, hasVictims, people killed in bombing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVictims Context triple: [McNamara brothers bombing case, hasVictims, people killed in bombing]
-
A.
mainVictims
Indicates that the related entities are the primary or principal targets harmed or affected by an action, event, or perpetrator.
-
B.
hasVictimCount
Indicates the number of victims associated with a particular event, action, or entity.
-
C.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
D.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
E.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
- 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_69bd4409b264819085ab855f3eb5381a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e01872c81909607010c10538ad1 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2375a4819098e16acb982c8fab |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dfff1488190a32bbb615bfab970 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:25 p.m.