Triple
T3650004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Hollywood shootout |
E77395
|
entity |
| Predicate | casualtiesCiviliansInjured |
P34803
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [North Hollywood shootout, casualtiesCiviliansInjured, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesCiviliansInjured Context triple: [North Hollywood shootout, casualtiesCiviliansInjured, 8]
-
A.
casualtiesCiviliansWounded
chosen
Indicates that an event or action resulted in civilian individuals being wounded or injured.
-
B.
casualtiesCiviliansKilled
Indicates that the relationship records the number of civilian deaths resulting from a specific event or action.
-
C.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
D.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
E.
casualtiesImpact
Indicates how the number or severity of casualties affects or influences another factor, situation, or outcome.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc38fa1988190b630329700afc3dd |
completed | March 8, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69adb8445b2c8190ab07f6ad4e010d0e |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.