Triple
T25223665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenya McQueen |
E632030
|
entity |
| Predicate | screenTimeProportion |
P158045
|
FINISHED |
| Object | appears in most scenes of Something New |
—
|
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: appears in most scenes of Something New | Statement: [Kenya McQueen, screenTimeProportion, appears in most scenes of Something New]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screenTimeProportion Context triple: [Kenya McQueen, screenTimeProportion, appears in most scenes of Something New]
-
A.
screenTime
Indicates the amount of time an entity spends viewing or interacting with a screen-based device.
-
B.
screenTimeRelation
Indicates a relationship between entities based on the amount, duration, or pattern of time spent using screens or digital devices.
-
C.
screenTimeFunction
Indicates a functional relationship that maps an entity (such as a user, device, or app) to the amount of time its screen is active or in use.
-
D.
screenTimeLevel
Indicates the degree or amount of time an entity spends using screens or digital devices.
-
E.
screenTimePhase
Indicates the specific stage or period within a broader screen-time process, session, or lifecycle that an entity is currently in.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f47cc166548190898ef3bd661ddb58 |
completed | May 1, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f44d849e7c81909945438f40e35362 |
completed | May 1, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_69f45300bd488190bb1d4160f5534ef6 |
completed | May 1, 2026, 7:15 a.m. |
Created at: April 21, 2026, 1:03 p.m.