Triple
T17262814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sadiki College |
E419047
|
entity |
| Predicate | hasAlumnus |
P51
|
FINISHED |
| Object | Hédi Chaker |
E1254623
|
NE FINISHED |
How this triple was built (2 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: Hédi Chaker | Statement: [Sadiki College, hasAlumnus, Hédi Chaker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hédi Chaker Context triple: [Sadiki College, hasAlumnus, Hédi Chaker]
-
A.
Hédi Chaker
chosen
Hédi Chaker was a prominent Tunisian nationalist leader and independence activist who played a key role in the country’s anti-colonial movement.
-
B.
Hédi Nouira
Hédi Nouira was a prominent Tunisian politician who served as Prime Minister from 1970 to 1980 and played a key role in shaping the country’s post-independence economic policies.
-
C.
Chadlia Saïda Farhat
Chadlia Saïda Farhat was the First Lady of Tunisia during the presidency of her husband, Beji Caid Essebsi.
-
D.
Aida El-Kachef
Aida El-Kachef is known as the wife of Egyptian diplomat and Nobel Peace Prize laureate Mohamed ElBaradei.
-
E.
Samia Chancrin
Samia Chancrin is an actress known for her role in the German crime thriller film "In the Fade."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_6a0180ce69d08190aa254f219a572a92 |
completed | May 11, 2026, 7:10 a.m. |
Created at: April 10, 2026, 5:40 a.m.