Triple
T17663648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maradona by Kusturica |
E440314
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
María José Martínez
María José Martínez is a film producer known for her work on the documentary "Maradona by Kusturica."
|
E1281662
|
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 José Martínez | Statement: [Maradona by Kusturica, producer, María José Martínez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: María José Martínez Context triple: [Maradona by Kusturica, producer, María José Martínez]
-
A.
Ifigenia Martínez
Ifigenia Martínez is a Mexican economist, diplomat, and left-wing politician best known as one of the founding figures of modern progressive politics in Mexico.
-
B.
Marian Álvarez
Marian Álvarez is a Spanish film and television actress known for her intense dramatic roles and critically acclaimed performances.
-
C.
María Isabel Nadal
María Isabel Nadal is the younger sister of Spanish tennis champion Rafael Nadal, known for maintaining a relatively private life despite her brother’s global fame.
-
D.
Silvia Pérez
Silvia Pérez is an actress known for her role in the Argentine film "Tetro," directed by Francis Ford Coppola.
-
E.
Rafaela Barrera
Rafaela Barrera is a barangay (village-level administrative division) within the city of Sagay in the Philippines.
- 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 José Martínez Triple: [Maradona by Kusturica, producer, María José Martínez]
Generated description
María José Martínez is a film producer known for her work on the documentary "Maradona by Kusturica."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: María José Martínez Target entity description: María José Martínez is a film producer known for her work on the documentary "Maradona by Kusturica."
-
A.
Ifigenia Martínez
Ifigenia Martínez is a Mexican economist, diplomat, and left-wing politician best known as one of the founding figures of modern progressive politics in Mexico.
-
B.
Marian Álvarez
Marian Álvarez is a Spanish film and television actress known for her intense dramatic roles and critically acclaimed performances.
-
C.
María Isabel Nadal
María Isabel Nadal is the younger sister of Spanish tennis champion Rafael Nadal, known for maintaining a relatively private life despite her brother’s global fame.
-
D.
Silvia Pérez
Silvia Pérez is an actress known for her role in the Argentine film "Tetro," directed by Francis Ford Coppola.
-
E.
Rafaela Barrera
Rafaela Barrera is a barangay (village-level administrative division) within the city of Sagay in the Philippines.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea7f0ec81908eff43aa845584af |
completed | April 19, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02165c9a4481909a6c43b2b58e1fc8 |
completed | May 11, 2026, 5:48 p.m. |
| NEDg | Description generation | batch_6a021f80092c81909a1827561ed69f17 |
completed | May 11, 2026, 6:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a021fe90da48190810c7aa2c2de2801 |
completed | May 11, 2026, 6:28 p.m. |
Created at: April 10, 2026, 9:53 a.m.