Triple
T6248400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guillermo del Toro |
E139979
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Lorenza Newton |
E139979
|
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: Lorenza Newton | Statement: [Guillermo del Toro, spouse, Lorenza Newton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorenza Newton Context triple: [Guillermo del Toro, spouse, Lorenza Newton]
-
A.
Lorenza Newton
chosen
Lorenza Newton is a Mexican art designer and the longtime wife of acclaimed filmmaker Guillermo del Toro.
-
B.
Jess Newton
Jess Newton is a fictional or dramatized member of the Newton Boys gang, depicted as one of the train- and bank-robbing outlaws in the film "The Newton Boys."
-
C.
Denisia Andrews
Denisia Andrews is a contemporary songwriter best known for co-writing major R&B and pop hits, including Beyoncé’s song “Cuff It.”
-
D.
Celeste Wright
Celeste Wright is a central character in the TV series "Big Little Lies," portrayed as a successful lawyer and seemingly perfect wife whose storyline explores the hidden trauma of domestic abuse.
-
E.
Lavender Thornton
Lavender Thornton is the wife of British politician and former Hong Kong governor Chris Patten.
- 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_69c008b4858c819095b0199114a9a87b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0633a9a048190856d5247d3b28a2e |
completed | March 22, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5191599d0819098a1b20b9d680f4b |
completed | March 26, 2026, 11:31 a.m. |
Created at: March 22, 2026, 4:24 p.m.