Triple
T8519391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benjamin Bratt |
E201657
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Talisa Soto |
E690378
|
NE 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: Talisa Soto | Statement: [Benjamin Bratt, spouse, Talisa Soto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talisa Soto Context triple: [Benjamin Bratt, spouse, Talisa Soto]
-
A.
Talisa Soto
chosen
Talisa Soto is an American actress and former model best known for her roles in films such as the James Bond movie "Licence to Kill" and the "Mortal Kombat" series.
-
B.
Sofia Arreguin
Sofia Arreguin is a member of the creative collective or group known as Wand.
-
C.
Lola Salazar
Lola Salazar is a fictional character appearing in the narrative of *The Wolf Song*.
-
D.
Celina Carvajal
Celina Carvajal, also known professionally as Lena Hall, is a Tony Award–winning American actress and singer best known for her work in Broadway musicals and rock-inspired performances.
-
E.
Tatiana Gutierrez
Tatiana Gutierrez is a recurring nurse character in The Evil Within survival horror video game series, serving as a mysterious guide and save-point attendant for the protagonist within the STEM world.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe627de908190b463da0f26da4ffb |
completed | March 31, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf5139150081909a020db7ca4bccc3 |
completed | April 3, 2026, 5:33 a.m. |
Created at: March 30, 2026, 6:16 p.m.