Triple
T3760392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miracle Max |
E82145
|
entity |
| Predicate | screenTimeCharacteristic |
P42651
|
FINISHED |
| Object | supporting character |
—
|
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: supporting character | Statement: [Miracle Max, screenTimeCharacteristic, supporting character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screenTimeCharacteristic Context triple: [Miracle Max, screenTimeCharacteristic, supporting character]
-
A.
screenTimeImportance
Indicates how important or significant the amount of time spent using screens or digital devices is considered in a given context.
-
B.
powerCharacteristic
Indicates a relationship where one entity has a specific power-related property, capacity, or performance attribute characterized by the other entity.
-
C.
trainingCharacteristic
Indicates that an entity has a specific property, feature, or quality related to training (such as method, intensity, or style).
-
D.
sessionLength
Indicates the duration of time that a particular session lasts from start to end.
-
E.
timeCharacteristic
chosen
Indicates a relationship where one entity specifies a temporal property, feature, or constraint that characterizes another entity or event.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbc3d3f48190974cec104080949f |
completed | March 8, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69adc04c851c8190ae5eaebf36df539b |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.