Triple
T17977417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Will Salas |
E449511
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Rachel Salas |
—
|
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: Rachel Salas | Statement: [Will Salas, mother, Rachel Salas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachel Salas Context triple: [Will Salas, mother, Rachel Salas]
-
A.
Rachel Salas
Rachel Salas is a central character in the science-fiction film "In Time," portrayed as the wealthy and protective mother of Sylvia Weis.
-
B.
Rachel Salas
chosen
Rachel Salas is a fictional character from the science fiction film "In Time," known as the mother of the protagonist Will Salas.
-
C.
Michelle Salas
Michelle Salas is a Mexican fashion influencer and model, best known as the daughter of singer Luis Miguel and actress Stephanie Salas.
-
D.
Lisa Benavides
Lisa Benavides is an American actress known for her work in independent films and as the wife of actor-director Tim Blake Nelson.
-
E.
Marisa Ramirez
Marisa Ramirez is an American actress best known for her role as Detective Maria Baez on the television series "Blue Bloods."
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b200e9108190bcdde5ba7938ba94 |
completed | April 19, 2026, 10:44 a.m. |
Created at: April 10, 2026, 10:22 a.m.