Triple
T10453828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York State Summer School of the Arts |
E246499
|
entity |
| Predicate | participantAgeGroup |
P19123
|
FINISHED |
| Object | teenagers |
—
|
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: teenagers | Statement: [New York State Summer School of the Arts, participantAgeGroup, teenagers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: participantAgeGroup Context triple: [New York State Summer School of the Arts, participantAgeGroup, teenagers]
-
A.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
B.
ageGroup
chosen
Indicates the categorical age range or bracket to which an entity belongs.
-
C.
inUniverseAgeGroup
Indicates that an entity belongs to a specified age group within a particular fictional or defined universe or setting.
-
D.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
E.
attractsAgeGroup
Indicates that something tends to draw interest or appeal from people belonging to a particular 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe0d73d48190acb687b96918e0cf |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb7d353c8190a73f439a956c7606 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:17 p.m.