Triple
T17262834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sadiki College |
E419047
|
entity |
| Predicate | hasAlumnus |
P51
|
FINISHED |
| Object |
Slim Chaker
Slim Chaker was a Tunisian politician who served in several ministerial roles, including as Minister of Finance and Minister of Public Health.
|
E1258445
|
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: Slim Chaker | Statement: [Sadiki College, hasAlumnus, Slim Chaker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slim Chaker Context triple: [Sadiki College, hasAlumnus, Slim Chaker]
-
A.
Rami Shakarchi
Rami Shakarchi is a mathematician and educator best known for coauthoring with Elias Stein a widely used series of graduate-level textbooks on analysis.
-
B.
Joe Mimran
Joe Mimran is a Canadian fashion designer and entrepreneur best known for creating influential lifestyle brands such as Club Monaco and Joe Fresh.
-
C.
Jeremy Chatzky
Jeremy Chatzky is an American bassist best known for his work with Bruce Springsteen’s Sessions Band and other rock and folk artists.
-
D.
Sam Alayan
Sam Alayan is a musician best known as a member of the rock band Scars on Broadway.
-
E.
Paul Chahidi
Paul Chahidi is a British actor known for his work in film, television, and theatre, including roles in political satire and period dramas.
- 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: Slim Chaker Triple: [Sadiki College, hasAlumnus, Slim Chaker]
Generated description
Slim Chaker was a Tunisian politician who served in several ministerial roles, including as Minister of Finance and Minister of Public Health.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Slim Chaker Target entity description: Slim Chaker was a Tunisian politician who served in several ministerial roles, including as Minister of Finance and Minister of Public Health.
-
A.
Rami Shakarchi
Rami Shakarchi is a mathematician and educator best known for coauthoring with Elias Stein a widely used series of graduate-level textbooks on analysis.
-
B.
Joe Mimran
Joe Mimran is a Canadian fashion designer and entrepreneur best known for creating influential lifestyle brands such as Club Monaco and Joe Fresh.
-
C.
Jeremy Chatzky
Jeremy Chatzky is an American bassist best known for his work with Bruce Springsteen’s Sessions Band and other rock and folk artists.
-
D.
Sam Alayan
Sam Alayan is a musician best known as a member of the rock band Scars on Broadway.
-
E.
Paul Chahidi
Paul Chahidi is a British actor known for his work in film, television, and theatre, including roles in political satire and period dramas.
- 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_6a0171041f2c81909bf52025d68912fc |
completed | May 11, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a0171c1b5fc81908455cda0df277ea9 |
completed | May 11, 2026, 6:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01724c4e34819099168d7303a31498 |
completed | May 11, 2026, 6:08 a.m. |
Created at: April 10, 2026, 5:40 a.m.