Triple
T13070162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anpanman picture books |
E329433
|
entity |
| Predicate | intendedReadingContext |
P20179
|
FINISHED |
| Object | home |
—
|
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: home | Statement: [Anpanman picture books, intendedReadingContext, home]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedReadingContext Context triple: [Anpanman picture books, intendedReadingContext, home]
-
A.
readingContext
Indicates the situational or surrounding information (such as location, time, or medium) within which a reading activity or act of reading takes place.
-
B.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
-
C.
intendedTargetContext
Indicates the context, situation, or setting that an action, message, or object is specifically designed or meant to be used in or directed toward.
-
D.
intendedInterpretation
Indicates that one entity is meant to be understood or interpreted in a particular way, sense, or meaning relative to another.
-
E.
intendedReadingLevel
chosen
Indicates the reading proficiency or audience level that a text or resource is designed or meant to be understood by.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ee6130819095d835e7ff6a8c5b |
completed | April 10, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9 p.m.