Triple
T14692334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attorney General of the Gambia |
E345064
|
entity |
| Predicate | officeHolders |
P9949
|
FINISHED |
| Object |
Marie Saine-Firdaus
Marie Saine-Firdaus is a Gambian lawyer and politician who served as the country's Attorney General and Minister of Justice.
|
E1168991
|
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: Marie Saine-Firdaus | Statement: [Attorney General of the Gambia, officeHolders, Marie Saine-Firdaus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marie Saine-Firdaus Context triple: [Attorney General of the Gambia, officeHolders, Marie Saine-Firdaus]
-
A.
Marie Gillain
Marie Gillain is a Belgian actress known for her roles in European cinema, particularly in French-language films.
-
B.
Marcelle Hainia
Marcelle Hainia was a French actress known for her role in the classic 1932 film "Boudu Saved from Drowning."
-
C.
Marie Roche
Marie Roche was the wife of Henry Fielding Dickens, a British barrister and son of the novelist Charles Dickens.
-
D.
Marie Janson
Marie Janson was a pioneering Belgian socialist politician, known as the first woman to serve in the Belgian Senate.
-
E.
Marcelle Maurette
Marcelle Maurette was a French playwright best known for her stage works about historical figures, particularly her play about the Grand Duchess Anastasia that inspired the 1956 film adaptation.
- 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: Marie Saine-Firdaus Triple: [Attorney General of the Gambia, officeHolders, Marie Saine-Firdaus]
Generated description
Marie Saine-Firdaus is a Gambian lawyer and politician who served as the country's Attorney General and Minister of Justice.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marie Saine-Firdaus Target entity description: Marie Saine-Firdaus is a Gambian lawyer and politician who served as the country's Attorney General and Minister of Justice.
-
A.
Marie Gillain
Marie Gillain is a Belgian actress known for her roles in European cinema, particularly in French-language films.
-
B.
Marcelle Hainia
Marcelle Hainia was a French actress known for her role in the classic 1932 film "Boudu Saved from Drowning."
-
C.
Marie Roche
Marie Roche was the wife of Henry Fielding Dickens, a British barrister and son of the novelist Charles Dickens.
-
D.
Marie Janson
Marie Janson was a pioneering Belgian socialist politician, known as the first woman to serve in the Belgian Senate.
-
E.
Marcelle Maurette
Marcelle Maurette was a French playwright best known for her stage works about historical figures, particularly her play about the Grand Duchess Anastasia that inspired the 1956 film adaptation.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb585d46c81908d6964130914cec4 |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff677b7be08190afc2767835836908 |
completed | May 9, 2026, 4:57 p.m. |
| NEDg | Description generation | batch_69ff67f64d2c81908fd2d8a09cd0b369 |
completed | May 9, 2026, 4:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff6888a85481909e8cdd34ed230fa4 |
completed | May 9, 2026, 5:02 p.m. |
Created at: April 10, 2026, 1:28 a.m.