Triple
T16253149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Monster |
E394561
|
entity |
| Predicate | targetDemographicOfWork |
P61787
|
FINISHED |
| Object | young 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: young adult readers | Statement: [The Monster, targetDemographicOfWork, young adult readers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetDemographicOfWork Context triple: [The Monster, targetDemographicOfWork, young adult readers]
-
A.
targetAudienceOfOriginWork
chosen
Indicates the intended audience or demographic group for which the original work was created.
-
B.
targetWork
Indicates that one entity is the specific work (e.g., document, artwork, or project) that another entity is directed at, refers to, or is primarily concerned with.
-
C.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
D.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
E.
employerFocus
Indicates that an employer directs particular attention, resources, or priority toward a specific subject, group, or area.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24597b74481908fdb8175628a57a1 |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.