Triple
T24912322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Girlfriend Experience (TV series) |
E623877
|
entity |
| Predicate | firstSeasonLeadActor |
P166850
|
FINISHED |
| Object | Riley Keough |
—
|
NE NERFINISHED |
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: Riley Keough | Statement: [The Girlfriend Experience (TV series), firstSeasonLeadActor, Riley Keough]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstSeasonLeadActor Context triple: [The Girlfriend Experience (TV series), firstSeasonLeadActor, Riley Keough]
-
A.
originalLeadActorRole
Indicates the role originally played by a particular lead actor in a given production or work.
-
B.
leadRoleActor
chosen
Indicates that an actor performs a leading or principal role in a work or production.
-
C.
firstSeriesRegular
Indicates that an entity is the first person to serve as a series regular in a given series or show.
-
D.
leadActorDebutFilmFor
Indicates that a person’s first film as a lead actor is the specified movie.
-
E.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
- 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_69e2fac889c081908e9ff686cb428e5a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 18, 2026, 5:28 a.m.