Triple
T14781409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rojo |
E347396
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
María Rojo
María Rojo is a renowned Mexican actress and politician known for her work in film, television, and public service.
|
E1183054
|
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: María Rojo | Statement: [Rojo, hasNotableBearer, María Rojo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: María Rojo Context triple: [Rojo, hasNotableBearer, María Rojo]
-
A.
María Navarro
María Navarro is a Spanish-language given name and surname combination shared by various notable figures in fields such as politics, academia, and the arts.
-
B.
Rosa García
Rosa García is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname García.
-
C.
Carmen Calvo
Carmen Calvo is a Spanish conceptual artist known for her evocative mixed-media works that explore memory, identity, and the passage of time.
-
D.
María Sol
María Sol is the younger sister of Argentine football star Lionel Messi and a member of the well-known Messi family.
-
E.
María Cortés
María Cortés was a daughter of the Spanish conquistador Hernán Cortés, belonging to the colonial-era lineage that emerged from his conquests in the Americas.
- 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: María Rojo Triple: [Rojo, hasNotableBearer, María Rojo]
Generated description
María Rojo is a renowned Mexican actress and politician known for her work in film, television, and public service.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: María Rojo Target entity description: María Rojo is a renowned Mexican actress and politician known for her work in film, television, and public service.
-
A.
María Navarro
María Navarro is a Spanish-language given name and surname combination shared by various notable figures in fields such as politics, academia, and the arts.
-
B.
Rosa García
Rosa García is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname García.
-
C.
Carmen Calvo
Carmen Calvo is a Spanish conceptual artist known for her evocative mixed-media works that explore memory, identity, and the passage of time.
-
D.
María Sol
María Sol is the younger sister of Argentine football star Lionel Messi and a member of the well-known Messi family.
-
E.
María Cortés
María Cortés was a daughter of the Spanish conquistador Hernán Cortés, belonging to the colonial-era lineage that emerged from his conquests in the Americas.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9de3f48190b7706925e2947cf5 |
completed | April 14, 2026, 11:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb02d84d881909aa8a1a3653d37bf |
completed | May 9, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69ffb25001d08190abcabfb6ce0e1029 |
completed | May 9, 2026, 10:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb2ab22dc8190b8cb0403ec0a09c4 |
completed | May 9, 2026, 10:18 p.m. |
Created at: April 10, 2026, 1:31 a.m.