Triple
T19456346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ônibus 174 |
E486741
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Elena Soárez
Elena Soárez is a Brazilian screenwriter best known for co-writing the acclaimed documentary film "Ônibus 174."
|
E1380108
|
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: Elena Soárez | Statement: [Ônibus 174, writer, Elena Soárez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elena Soárez Context triple: [Ônibus 174, writer, Elena Soárez]
-
A.
Elena Alvarez
Elena Alvarez is a socially conscious, feminist teenage daughter in the Cuban-American family at the heart of the sitcom "One Day at a Time" (2017).
-
B.
Elena Ruiz
Elena Ruiz is a film editor best known for her work on the acclaimed Spanish horror film "The Orphanage."
-
C.
Daniella García
Daniella García is a member of the García-Lorido family, known for its ties to the entertainment industry through actor Andy García and actress Dominik García-Lorido.
-
D.
Yara Martinez
Yara Martinez is an American television and film actress known for her roles in series such as "Jane the Virgin," "The Tick," and "Bull."
-
E.
Selenis Leyva
Selenis Leyva is a Cuban-American actress best known for her role as Gloria Mendoza on the Netflix series "Orange Is the New Black."
- 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: Elena Soárez Triple: [Ônibus 174, writer, Elena Soárez]
Generated description
Elena Soárez is a Brazilian screenwriter best known for co-writing the acclaimed documentary film "Ônibus 174."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elena Soárez Target entity description: Elena Soárez is a Brazilian screenwriter best known for co-writing the acclaimed documentary film "Ônibus 174."
-
A.
Elena Alvarez
Elena Alvarez is a socially conscious, feminist teenage daughter in the Cuban-American family at the heart of the sitcom "One Day at a Time" (2017).
-
B.
Elena Ruiz
Elena Ruiz is a film editor best known for her work on the acclaimed Spanish horror film "The Orphanage."
-
C.
Daniella García
Daniella García is a member of the García-Lorido family, known for its ties to the entertainment industry through actor Andy García and actress Dominik García-Lorido.
-
D.
Yara Martinez
Yara Martinez is an American television and film actress known for her roles in series such as "Jane the Virgin," "The Tick," and "Bull."
-
E.
Selenis Leyva
Selenis Leyva is a Cuban-American actress best known for her role as Gloria Mendoza on the Netflix series "Orange Is the New Black."
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c4088881908f23f25a82a513f6 |
completed | April 20, 2026, 2:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07470ff794819098bb55f51cd32c4b |
completed | May 15, 2026, 4:17 p.m. |
| NEDg | Description generation | batch_6a0747f6b1d48190a3e70576ddb4feb2 |
completed | May 15, 2026, 4:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07492259488190a8c405598f9c8878 |
completed | May 15, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:38 p.m.