Triple
T29720469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shooting of Amadou Diallo |
E752043
|
entity |
| Predicate | involvedOfficer |
P187044
|
FINISHED |
| Object | Sean Carroll |
—
|
NE NERFINISHED |
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: Sean Carroll | Statement: [Shooting of Amadou Diallo, involvedOfficer, Sean Carroll]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedOfficer Context triple: [Shooting of Amadou Diallo, involvedOfficer, Sean Carroll]
-
A.
lawEnforcementInvolved
Indicates that law enforcement authorities are actively involved in or responding to the situation or event described.
-
B.
formerlyInvolved
Indicates that an entity previously participated in or was associated with another entity or activity, but is no longer involved.
-
C.
officersAre
Indicates that certain individuals hold the role or position of officers within a specified group, organization, or context.
-
D.
frontInvolved
Indicates that an entity is directly involved in or associated with the front (e.g., front line, front-facing part, or leading edge) of another entity or situation.
-
E.
hasAuthorityInvolved
Indicates that an authority or official body is involved in, oversees, or has jurisdiction over the referenced situation or relationship.
- 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_69f0d628c00c8190ab5ee7e423d7ec3c |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
| PDg | Predicate description generation | batch_69fb3424724c8190ba55ecf66fa0b171 |
completed | May 6, 2026, 12:29 p.m. |
Created at: April 28, 2026, 7:36 p.m.