Triple
T27848074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Today I Feel Silly: And Other Moods That Make My Day |
E703877
|
entity |
| Predicate | readerAgeRange |
P102642
|
FINISHED |
| Object | early elementary school children |
—
|
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: early elementary school children | Statement: [Today I Feel Silly: And Other Moods That Make My Day, readerAgeRange, early elementary school children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readerAgeRange Context triple: [Today I Feel Silly: And Other Moods That Make My Day, readerAgeRange, early elementary school children]
-
A.
hasProtagonistAgeRange
Indicates that a work’s main character falls within a specified age range.
-
B.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
C.
fictionalAgeRange
Indicates the span of ages a fictional character or entity is depicted as having within a narrative or fictional context.
-
D.
typicalAge
Indicates the usual or characteristic age associated with an entity, event, or condition.
-
E.
intendedForAgeGroup
chosen
Indicates that something is designed, suitable, or targeted for use by a specific age group.
- 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63902f71c8190b26ac186ad00acbf |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f6318ae6f08190b3f85f9201046a15 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 6:08 p.m.