Triple
T4372062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aureliano Buendía |
E98918
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Rebeca |
E37539
|
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: Rebeca | Statement: [Aureliano Buendía, relative, Rebeca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rebeca Context triple: [Aureliano Buendía, relative, Rebeca]
-
A.
Rebeca
chosen
Rebeca is a feminine given name, commonly used in Spanish- and Portuguese-speaking countries, that is a variant of the name Rebecca.
-
B.
Becca
Becca is a central character in the 2015 horror film "The Visit," a teenage girl who documents her and her brother’s unsettling stay with their estranged grandparents.
-
C.
Rachele
Rachele is an Italian given name, notably borne by Rachele Mussolini, the wife of dictator Benito Mussolini.
-
D.
Danielle
"Danielle" is a work created by Sarah Churchill, known as part of her contributions to the arts.
-
E.
Nina
Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
- 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_69b3454db3708190aeafd814413c4c3d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3521dffbc8190b9300a7f4f64bdc0 |
completed | March 12, 2026, 11:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e50ec35481908cf1e1afffda19cb |
completed | March 14, 2026, 10:45 p.m. |
Created at: March 12, 2026, 11:17 p.m.