Triple
T20493260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caer en tentación |
E502801
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Giselle González
Giselle González is a Mexican television producer best known for creating and producing successful telenovelas for Televisa.
|
E1514367
|
NE FINISHED |
How this triple was built (4 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: Giselle González | Statement: [Caer en tentación, executiveProducer, Giselle González]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Giselle González Context triple: [Caer en tentación, executiveProducer, Giselle González]
-
A.
Brisa Carrillo
Brisa Carrillo is a Mexican actress and singer best known for her work in telenovelas and youth-oriented television series.
-
B.
Clara Almanzar
Clara Almanzar is the mother of rapper Cardi B and the maternal grandmother of Cardi B’s daughter, Kulture Kiari Cephus.
-
C.
Jacqueline García
Jacqueline García is a Mexican actress best known for her roles in popular telenovelas.
-
D.
Macarena García
Macarena García is a Spanish actress best known for her acclaimed performance in the silent black-and-white film "Blancanieves."
-
E.
Cecilia Muñoz
Cecilia Muñoz is an American public policy expert and former Obama administration official known for her leadership on immigration and domestic policy issues.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Giselle González Triple: [Caer en tentación, executiveProducer, Giselle González]
Generated description
Giselle González is a Mexican television producer best known for creating and producing successful telenovelas for Televisa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Giselle González Target entity description: Giselle González is a Mexican television producer best known for creating and producing successful telenovelas for Televisa.
-
A.
Brisa Carrillo
Brisa Carrillo is a Mexican actress and singer best known for her work in telenovelas and youth-oriented television series.
-
B.
Clara Almanzar
Clara Almanzar is the mother of rapper Cardi B and the maternal grandmother of Cardi B’s daughter, Kulture Kiari Cephus.
-
C.
Jacqueline García
Jacqueline García is a Mexican actress best known for her roles in popular telenovelas.
-
D.
Macarena García
Macarena García is a Spanish actress best known for her acclaimed performance in the silent black-and-white film "Blancanieves."
-
E.
Cecilia Muñoz
Cecilia Muñoz is an American public policy expert and former Obama administration official known for her leadership on immigration and domestic policy issues.
- F. None of above. chosen
Provenance (5 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbb3bd081909351525208b41bba |
completed | April 20, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a735b9e5881909ec8672fd82c1068 |
completed | May 18, 2026, 2:03 a.m. |
| NEDg | Description generation | batch_6a0a74e81da881908c73d864258dcdd5 |
completed | May 18, 2026, 2:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a75cbb2408190b058713432b048a2 |
completed | May 18, 2026, 2:13 a.m. |
Created at: April 16, 2026, 11:35 a.m.