Triple
T23324095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WeCrashed |
E591239
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | America Ferrera |
—
|
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: America Ferrera | Statement: [WeCrashed, stars, America Ferrera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: America Ferrera Context triple: [WeCrashed, stars, America Ferrera]
-
A.
America Ferrera
chosen
America Ferrera is an American actress and producer best known for her breakthrough title role in the television series "Ugly Betty" and for her work in film, television, and advocacy for Latinx representation.
-
B.
Leticia Ferrer
Leticia Ferrer is the daughter of renowned American acting teacher and actress Uta Hagen.
-
C.
Giovanna Ferrer
Giovanna Ferrer is the wife of Sean Hepburn Ferrer, the son of actress Audrey Hepburn and actor Mel Ferrer.
-
D.
Lorena Bernal
Lorena Bernal is an Argentine-born Spanish actress, model, and former Miss Spain who has also worked as a television presenter.
-
E.
Claudia Islas
Claudia Islas is a Mexican actress best known for her prominent roles in telenovelas and films during the 1970s and 1980s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d1effe4819096907f95f610dbff |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19787ee90819083416193efaab20f |
completed | April 29, 2026, 5:30 a.m. |
Created at: April 17, 2026, 5:08 p.m.