Triple
T834541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In Evil Hour |
E18040
|
entity |
| Predicate | hasIntendedAudience |
P793
|
FINISHED |
| Object | adult readers |
—
|
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: adult readers | Statement: [In Evil Hour, hasIntendedAudience, adult readers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntendedAudience Context triple: [In Evil Hour, hasIntendedAudience, adult readers]
-
A.
hasAudience
chosen
Indicates that an entity is intended to be received, viewed, or engaged with by a particular group of people.
-
B.
hasEducationalAudience
Indicates that something is intended for or directed toward a specific educational audience or learner group.
-
C.
isSuitableFor
Indicates that one entity is appropriate, fitting, or well-matched for use, application, or association with another entity.
-
D.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
E.
hasAudienceSize
Indicates the relationship between an entity and the number of people or size of group that receives, views, or engages with it.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abccb94881909cd49aa3fd986b4a |
completed | March 1, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7c7df881909c539c3ab8ff0367 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.