Triple
T21799490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johnny "Drama" Chase |
E538197
|
entity |
| Predicate | oftenSeenDoing |
P1164
|
FINISHED |
| Object | auditioning for acting roles |
—
|
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: auditioning for acting roles | Statement: [Johnny "Drama" Chase, oftenSeenDoing, auditioning for acting roles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenSeenDoing Context triple: [Johnny "Drama" Chase, oftenSeenDoing, auditioning for acting roles]
-
A.
typicalActivity
chosen
Indicates that an entity is commonly or characteristically engaged in a particular activity.
-
B.
activitiesCarriedOutFor
Indicates that certain activities are performed on behalf of, in service of, or for the benefit of a particular entity.
-
C.
otherActivity
Indicates that an entity is engaged in an activity that is different from a primary, specified, or expected activity.
-
D.
activityType
Indicates the specific kind or category of action or event that an entity is engaged in or associated with.
-
E.
activityCorrelatesWith
Indicates that the level or occurrence of one activity is statistically associated with the level or occurrence of another activity, without implying direct causation.
- 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f077fd59048190ae4e50f4aee919e7 |
completed | April 28, 2026, 9:03 a.m. |
| PD | Predicate disambiguation | batch_69e6be751ce881909badced245ef76c7 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:53 p.m.