Triple
T10091317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SENTRI |
E215349
|
entity |
| Predicate | screeningIncludes |
P79747
|
FINISHED |
| Object | criminal history check |
—
|
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: criminal history check | Statement: [SENTRI, screeningIncludes, criminal history check]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screeningIncludes Context triple: [SENTRI, screeningIncludes, criminal history check]
-
A.
screeningType
Indicates the specific method or category of screening applied in a screening process or evaluation.
-
B.
screeningBasis
chosen
Indicates the underlying reason, criterion, or grounds on which a screening or evaluation is conducted between entities.
-
C.
screeningTime
Indicates the scheduled time at which a screening (such as a film, show, or test) is set to occur.
-
D.
screeningVenue
Indicates the place or location where a screening (such as a film or event showing) takes place.
-
E.
seriesIncludes
Indicates that a particular series contains or encompasses the referenced item as one of its constituent parts.
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd05aa02081908fba02e7085c6d7c |
completed | April 2, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:01 p.m.