Triple
T15613402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rafael Pérez |
E375353
|
entity |
| Predicate | effectOfActions |
P103507
|
FINISHED |
| Object | triggered major investigations into LAPD practices |
—
|
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: triggered major investigations into LAPD practices | Statement: [Rafael Pérez, effectOfActions, triggered major investigations into LAPD practices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOfActions Context triple: [Rafael Pérez, effectOfActions, triggered major investigations into LAPD practices]
-
A.
effectOfActivities
chosen
Indicates the causal impact that certain activities have on a particular outcome, state, or condition.
-
B.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
C.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
D.
predictedEffect
Indicates that one entity is expected to cause, influence, or result in a particular outcome or consequence for another entity.
-
E.
causeOfAction
Indicates that one entity is the reason or basis for initiating a legal action or lawsuit against another entity.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e83407c8190abbcd4b7fab0ff85 |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:13 a.m.