Triple
T17262817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sadiki College |
E419047
|
entity |
| Predicate | hasAlumnus |
P51
|
FINISHED |
| Object |
Mohamed Charfi
Mohamed Charfi was a prominent Tunisian jurist, academic, and reformist Minister of Education known for his advocacy of secularism, human rights, and educational modernization.
|
E1287002
|
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: Mohamed Charfi | Statement: [Sadiki College, hasAlumnus, Mohamed Charfi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mohamed Charfi Context triple: [Sadiki College, hasAlumnus, Mohamed Charfi]
-
A.
Tayeb Benamara
Tayeb Benamara is a French local politician who serves as the mayor of the suburban Paris commune of Le Blanc-Mesnil.
-
B.
Ichraf Chebil
Ichraf Chebil is a Tunisian magistrate best known as the wife of Tunisian President Kais Saied.
-
C.
Ahmed Hachani
Ahmed Hachani is a Tunisian politician who has served as head of government under President Kais Saied.
-
D.
Mohamed Ridouani
Mohamed Ridouani is a Belgian politician who serves as the mayor of the city of Leuven.
-
E.
Chafik Besseghier
Chafik Besseghier is a French figure skater known for competing internationally in men's singles, including appearances at European and World Championships.
- 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: Mohamed Charfi Triple: [Sadiki College, hasAlumnus, Mohamed Charfi]
Generated description
Mohamed Charfi was a prominent Tunisian jurist, academic, and reformist Minister of Education known for his advocacy of secularism, human rights, and educational modernization.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mohamed Charfi Target entity description: Mohamed Charfi was a prominent Tunisian jurist, academic, and reformist Minister of Education known for his advocacy of secularism, human rights, and educational modernization.
-
A.
Tayeb Benamara
Tayeb Benamara is a French local politician who serves as the mayor of the suburban Paris commune of Le Blanc-Mesnil.
-
B.
Ichraf Chebil
Ichraf Chebil is a Tunisian magistrate best known as the wife of Tunisian President Kais Saied.
-
C.
Ahmed Hachani
Ahmed Hachani is a Tunisian politician who has served as head of government under President Kais Saied.
-
D.
Mohamed Ridouani
Mohamed Ridouani is a Belgian politician who serves as the mayor of the city of Leuven.
-
E.
Chafik Besseghier
Chafik Besseghier is a French figure skater known for competing internationally in men's singles, including appearances at European and World Championships.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f4379848190add32ba8e5f93527 |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02efa45b8c81908d31f097b5c4712a |
completed | May 12, 2026, 9:15 a.m. |
| NEDg | Description generation | batch_6a02f1232f348190ab28e8d5ed4d3ad3 |
completed | May 12, 2026, 9:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a02f18beeb88190ac8cb9540b6b7b88 |
completed | May 12, 2026, 9:23 a.m. |
Created at: April 10, 2026, 5:40 a.m.