Triple
T21906309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darío Grandinetti |
E540946
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Rojo
Rojo is an Argentine film best known for featuring actor Darío Grandinetti in a prominent role.
|
E1507610
|
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: Rojo | Statement: [Darío Grandinetti, notableWork, Rojo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rojo Context triple: [Darío Grandinetti, notableWork, Rojo]
-
A.
Rojo
"Rojo" is a popular Spanish-language reggaeton song by Colombian artist J Balvin, known for its emotional tone and vivid red-themed visuals.
-
B.
Rojo
Rojo is a Spanish surname borne by various notable figures, including artists, politicians, and athletes.
-
C.
Vermelha
Vermelha is a civil parish located in the municipality of Cadaval in Portugal, known for its rural character within the Oeste region.
-
D.
Rosso
Rosso is the commonly used name of Rosso Fiorentino, a prominent Italian Mannerist painter of the early 16th century known for his expressive, unconventional style.
-
E.
Vermiglio
Vermiglio is a mountainous municipality in the Trentino region of northern Italy, known for its Alpine landscapes and proximity to major ski and hiking areas.
- 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: Rojo Triple: [Darío Grandinetti, notableWork, Rojo]
Generated description
Rojo is an Argentine film best known for featuring actor Darío Grandinetti in a prominent role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rojo Target entity description: Rojo is an Argentine film best known for featuring actor Darío Grandinetti in a prominent role.
-
A.
Rojo
"Rojo" is a popular Spanish-language reggaeton song by Colombian artist J Balvin, known for its emotional tone and vivid red-themed visuals.
-
B.
Rojo
Rojo is a Spanish surname borne by various notable figures, including artists, politicians, and athletes.
-
C.
Vermelha
Vermelha is a civil parish located in the municipality of Cadaval in Portugal, known for its rural character within the Oeste region.
-
D.
Rosso
Rosso is the commonly used name of Rosso Fiorentino, a prominent Italian Mannerist painter of the early 16th century known for his expressive, unconventional style.
-
E.
Vermiglio
Vermiglio is a mountainous municipality in the Trentino region of northern Italy, known for its Alpine landscapes and proximity to major ski and hiking areas.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f121d74d388190be58b937c486fa69 |
completed | April 28, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a5a08c4dc81908b7d90278ea4bc8c |
completed | May 18, 2026, 12:15 a.m. |
| NEDg | Description generation | batch_6a0a5ac52b588190b685aacc06cac3d0 |
completed | May 18, 2026, 12:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a5b7724188190bcdf44436cd8da26 |
completed | May 18, 2026, 12:21 a.m. |
Created at: April 16, 2026, 7:37 p.m.