Triple
T3053751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachida Brakni |
E60431
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Brakni
Brakni is the surname of Rachida Brakni, a French actress and director known for her work in film, television, and theater.
|
E322420
|
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: Brakni | Statement: [Rachida Brakni, familyName, Brakni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brakni Context triple: [Rachida Brakni, familyName, Brakni]
-
A.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
-
B.
Barellan
Barellan is a small rural town in the Riverina region of New South Wales, Australia, known for its grain farming and association with tennis champion Evonne Goolagong-Cawley.
-
C.
Raka
Raka is a renowned Afrikaans narrative poem by N. P. van Wyk Louw that explores themes of civilization, barbarism, and moral conflict through an allegorical tale.
-
D.
Bori
Bori is a prominent urban center in Nigeria’s Rivers State, serving as an important commercial and administrative hub for the surrounding region.
-
E.
Kharabali
Kharabali is a town in southern Russia that serves as an administrative and economic center within Astrakhan Oblast.
- 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: Brakni Triple: [Rachida Brakni, familyName, Brakni]
Generated description
Brakni is the surname of Rachida Brakni, a French actress and director known for her work in film, television, and theater.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brakni Target entity description: Brakni is the surname of Rachida Brakni, a French actress and director known for her work in film, television, and theater.
-
A.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
-
B.
Barellan
Barellan is a small rural town in the Riverina region of New South Wales, Australia, known for its grain farming and association with tennis champion Evonne Goolagong-Cawley.
-
C.
Raka
Raka is a renowned Afrikaans narrative poem by N. P. van Wyk Louw that explores themes of civilization, barbarism, and moral conflict through an allegorical tale.
-
D.
Bori
Bori is a prominent urban center in Nigeria’s Rivers State, serving as an important commercial and administrative hub for the surrounding region.
-
E.
Kharabali
Kharabali is a town in southern Russia that serves as an administrative and economic center within Astrakhan Oblast.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf51b5081908ce355a76cfa9e3c |
completed | March 8, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1ef00630c8190a3b5b2854350ecb9 |
completed | March 11, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69b1efa8c11081908661b33e465e11bc |
completed | March 11, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1f05e44e08190be8b194938b6c1c7 |
completed | March 11, 2026, 10:44 p.m. |
Created at: March 8, 2026, 3:01 p.m.