Triple
T21861173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jackson State killings |
E539763
|
entity |
| Predicate | hasNumberOfShotsFired |
P23883
|
FINISHED |
| Object | more than 150 rounds |
—
|
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: more than 150 rounds | Statement: [Jackson State killings, hasNumberOfShotsFired, more than 150 rounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfShotsFired Context triple: [Jackson State killings, hasNumberOfShotsFired, more than 150 rounds]
-
A.
numberOfShotsFired
chosen
Indicates the total count of shots that were discharged in the described event or action.
-
B.
noShotsFired
Indicates that in the referenced situation or interaction, no gunshots or firearm discharges occurred.
-
C.
hasChamberStatus
Indicates that an entity holds a particular status or condition within a specific chamber or legislative body.
-
D.
ammunitionCapacity
Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
-
E.
hasChamber
Indicates that one entity possesses, contains, or is associated with a distinct enclosed space or compartment (a chamber).
- 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_69e0c47829648190bbe2d1d7033768ec |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0d63ae3708190b7ee04c1487713c9 |
completed | April 28, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:56 p.m.