Triple
T36622238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Parley's Tales |
E904072
|
entity |
| Predicate | readerEngagementTechnique |
P128911
|
FINISHED |
| Object | direct address to the reader |
—
|
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: direct address to the reader | Statement: [Peter Parley's Tales, readerEngagementTechnique, direct address to the reader]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readerEngagementTechnique Context triple: [Peter Parley's Tales, readerEngagementTechnique, direct address to the reader]
-
A.
engagesAudienceAs
chosen
Indicates that one entity actively captures, involves, or holds the attention of an audience in the manner or role specified by another entity.
-
B.
readerReception
Indicates how readers interpret, respond to, or are affected by a particular text or work.
-
C.
readingApproach
Indicates the method, strategy, or manner in which an entity engages in reading a text.
-
D.
readingOf
Indicates that one entity is an interpretation, measurement, or recorded value derived from another entity.
-
E.
readingFeature
Indicates that an entity possesses a characteristic, capability, or attribute specifically related to reading.
- 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.