Triple
T19456390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mechanism |
E486742
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Elena Soarez |
—
|
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: Elena Soarez | Statement: [The Mechanism, creator, Elena Soarez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elena Soarez Context triple: [The Mechanism, creator, Elena Soarez]
-
A.
Elena Soárez
chosen
Elena Soárez is a Brazilian screenwriter best known for co-writing the acclaimed documentary film "Ônibus 174."
-
B.
Elena Alvarez
Elena Alvarez is a socially conscious, feminist teenage daughter in the Cuban-American family at the heart of the sitcom "One Day at a Time" (2017).
-
C.
Daniella Alonso
Daniella Alonso is an American actress and former fashion model known for her roles in television series such as "Revolution," "Dynasty," and various film and TV projects.
-
D.
Lisa Alvarado
Lisa Alvarado is a musician best known as a member of the experimental jazz collective Natural Information Society.
-
E.
Daniella García
Daniella García is a member of the García-Lorido family, known for its ties to the entertainment industry through actor Andy García and actress Dominik García-Lorido.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c4088881908f23f25a82a513f6 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:38 p.m.