Triple
T26115162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jodi Lyn O'Keefe |
E658803
|
entity |
| Predicate | notableGenreAsActress |
P41614
|
FINISHED |
| Object | teen film |
—
|
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: teen film | Statement: [Jodi Lyn O'Keefe, notableGenreAsActress, teen film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableGenreAsActress Context triple: [Jodi Lyn O'Keefe, notableGenreAsActress, teen film]
-
A.
notableStar
Indicates that the subject is a star (or stellar object) that is distinguished or noteworthy in some significant way, such as brightness, fame, or scientific interest, relative to other stars.
-
B.
actress
Indicates that the subject is a female performer who acts in films, television, theater, or other dramatic productions.
-
C.
portraysNotableAct
Indicates that an entity depicts or represents a significant or noteworthy action performed by another entity.
-
D.
actorNotableOccupation
Indicates that a person (typically an actor) is associated with a particular occupation or professional role for which they are especially well known.
-
E.
genreOfWorkActedIn
chosen
Indicates that an entity is the genre category of a work in which another entity performed or acted.
- 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_69ee5bc20298819099a42be042eb2349 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69fe610e1f6881908f10070ba64643cf |
completed | May 8, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69fe604c6c008190ad659e9b9fa82f7b |
completed | May 8, 2026, 10:14 p.m. |
Created at: April 26, 2026, 8:04 p.m.