Triple
T4450610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Úrsula Iguarán |
E97597
|
entity |
| Predicate | relativeOf |
P367
|
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: [Úrsula Iguarán, relativeOf, Rebeca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rebeca Context triple: [Úrsula Iguarán, relativeOf, 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 feminine given name used in various cultures, often as a short form of names like Antonina or Giannina, and borne by numerous notable figures in the arts and public life.
- 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_69b3454777808190b78aa9047ba1f018 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355f2377c8190b0176b4c6776815e |
completed | March 13, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6138b6c8c8190a21ad00fb230c0f0 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:33 p.m.