Triple
T16167151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Estefania Chiong Veloso |
E392333
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Estefania
Estefania is a feminine given name of Spanish origin commonly used in Spanish-speaking countries.
|
E1197493
|
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: Estefania | Statement: [Estefania Chiong Veloso, givenName, Estefania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Estefania Context triple: [Estefania Chiong Veloso, givenName, Estefania]
-
A.
Alejandra
Alejandra is the feminine given name corresponding to Alejandro, commonly used in Spanish-speaking cultures.
-
B.
Fabiola
Fabiola is a given name of Latin origin, historically associated with saints and European royalty.
-
C.
Rosa Elena
Rosa Elena is a Mexican public figure best known as the wife of former president Felipe Calderón and for her involvement in high-profile political and legal controversies.
-
D.
Graciela
Graciela is a feminine given name of Spanish origin, often considered a variant of Graziella and related to the concept of grace.
-
E.
Isela Vega
Isela Vega was a renowned Mexican actress, singer, and filmmaker known for her bold, groundbreaking roles in Mexican cinema and cult films of the 1970s.
- 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: Estefania Triple: [Estefania Chiong Veloso, givenName, Estefania]
Generated description
Estefania is a feminine given name of Spanish origin commonly used in Spanish-speaking countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Estefania Target entity description: Estefania is a feminine given name of Spanish origin commonly used in Spanish-speaking countries.
-
A.
Alejandra
Alejandra is the feminine given name corresponding to Alejandro, commonly used in Spanish-speaking cultures.
-
B.
Fabiola
Fabiola is a given name of Latin origin, historically associated with saints and European royalty.
-
C.
Rosa Elena
Rosa Elena is a Mexican public figure best known as the wife of former president Felipe Calderón and for her involvement in high-profile political and legal controversies.
-
D.
Graciela
Graciela is a feminine given name of Spanish origin, often considered a variant of Graziella and related to the concept of grace.
-
E.
Isela Vega
Isela Vega was a renowned Mexican actress, singer, and filmmaker known for her bold, groundbreaking roles in Mexican cinema and cult films of the 1970s.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb3ec4c81908d4e5c0f39a85900 |
completed | April 17, 2026, 11:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7b96bf08190b23bd3b705a34c61 |
completed | May 10, 2026, 3:12 a.m. |
| NEDg | Description generation | batch_69fff87caefc8190836d690dfb2523f9 |
completed | May 10, 2026, 3:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff98b3d7c8190bb284321d17f58e2 |
completed | May 10, 2026, 3:20 a.m. |
Created at: April 10, 2026, 5:02 a.m.