Triple
T36829378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Şahsiyet |
E910095
|
entity |
| Predicate | featuresFemaleDetective |
—
|
GENERATED |
| Object | true |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresFemaleDetective Context triple: [Şahsiyet, featuresFemaleDetective, true]
-
A.
featuresPrivateDetective
Indicates that the subject includes or involves a private detective as a notable element or character.
-
B.
detectiveType
Indicates that one entity is classified as a particular type or category of detective in relation to another entity.
-
C.
featuresDetectiveDuo
Indicates that the subject involves or centers around a pair of detectives working together as a team.
-
D.
hasFictionalDetective
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
-
E.
portrayedDetective
Indicates that one entity has played or depicted a detective character in a performance or work.
- F. None of above. chosen
Provenance (1 batch)
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_69f76e7e9d60819092442fba73290a46 |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:13 p.m.