Triple
T11015164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romo |
E260344
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
María Romo
María Romo is a Spanish actress known for her work in film and television.
|
E924001
|
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 Romo | Statement: [Romo, hasNotableBearer, María Romo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: María Romo Context triple: [Romo, hasNotableBearer, María Romo]
-
A.
María Valenzuela
María Valenzuela is an Argentine actress known for her extensive work in television, film, and theater across several decades.
-
B.
Maricruz Nájera
Maricruz Nájera is a Mexican actress known for her extensive work in film, television, and theater, and as part of a prominent acting family.
-
C.
Marisabel Rodríguez
Marisabel Rodríguez is a Venezuelan journalist and former First Lady of Venezuela, known for her marriage to President Hugo Chávez and her involvement in the country’s political and social life during his early years in power.
-
D.
Letícia Román
Letícia Román is an Italian actress best known for her roles in 1960s films, including opposite Elvis Presley in the musical comedy "G.I. Blues."
-
E.
Silvia Lemus
Silvia Lemus is a Mexican journalist and television host best known as the longtime wife and intellectual partner of celebrated writer Carlos Fuentes.
- 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 Romo Triple: [Romo, hasNotableBearer, María Romo]
Generated description
María Romo is a Spanish actress known for her work in film and television.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: María Romo Target entity description: María Romo is a Spanish actress known for her work in film and television.
-
A.
María Valenzuela
María Valenzuela is an Argentine actress known for her extensive work in television, film, and theater across several decades.
-
B.
Maricruz Nájera
Maricruz Nájera is a Mexican actress known for her extensive work in film, television, and theater, and as part of a prominent acting family.
-
C.
Marisabel Rodríguez
Marisabel Rodríguez is a Venezuelan journalist and former First Lady of Venezuela, known for her marriage to President Hugo Chávez and her involvement in the country’s political and social life during his early years in power.
-
D.
Letícia Román
Letícia Román is an Italian actress best known for her roles in 1960s films, including opposite Elvis Presley in the musical comedy "G.I. Blues."
-
E.
Silvia Lemus
Silvia Lemus is a Mexican journalist and television host best known as the longtime wife and intellectual partner of celebrated writer Carlos Fuentes.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797a558a08190bdb5779faa9adf05 |
completed | April 9, 2026, 12:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5b76fa8348190bb42f1c71eb0e545 |
completed | April 20, 2026, 5:19 a.m. |
| NEDg | Description generation | batch_69e5bb5d6e0c8190933cd3d6e83c24a2 |
completed | April 20, 2026, 5:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5c29d7b608190ae79bb8318211547 |
completed | April 20, 2026, 6:07 a.m. |
Created at: April 8, 2026, 9:25 p.m.