Triple
T10699214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonny Wortzik |
E252224
|
entity |
| Predicate | lawEnforcementOutcome |
P47732
|
FINISHED |
| Object | arrested at airport at end of film |
—
|
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: arrested at airport at end of film | Statement: [Sonny Wortzik, lawEnforcementOutcome, arrested at airport at end of film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawEnforcementOutcome Context triple: [Sonny Wortzik, lawEnforcementOutcome, arrested at airport at end of film]
-
A.
lawEnforcementResponse
Indicates the actions or measures taken by law enforcement agencies in reaction to an incident, behavior, or situation.
-
B.
lawEnforcementStatus
chosen
Indicates the relationship between an entity and its current standing or condition with respect to law enforcement, such as being under investigation, wanted, detained, or cleared.
-
C.
lawEnforcementLabel
Indicates that an entity has been designated, tagged, or classified by a law enforcement authority for monitoring, identification, or investigative purposes.
-
D.
legalOutcome
Indicates the resulting legal status, decision, or consequence that follows from a legal process, action, or judgment.
-
E.
lawEnforcementLevel
Indicates the degree or intensity of law enforcement presence, activity, or strictness applied in a given context.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd8abd7c81909c274aa1699a3695 |
completed | April 9, 2026, 1:14 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8cc0788190b4c02a772e4b58b3 |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:12 p.m.