Triple
T23370120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uproar |
E593445
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Olivier Bassil |
—
|
NE NERFINISHED |
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: Olivier Bassil | Statement: [Uproar, author, Olivier Bassil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olivier Bassil Context triple: [Uproar, author, Olivier Bassil]
-
A.
Olivier Bassil
chosen
Olivier Bassil is a writer known for his work on the project or publication "Uproar."
-
B.
Michel Aoun
Michel Aoun is a Lebanese military officer and politician who served as army commander, led a major anti-Syrian campaign during the late stages of the Lebanese Civil War, and later became President of Lebanon.
-
C.
Michael Boulos
Michael Boulos is a Lebanese-American business executive and heir to the Nigeria-based conglomerate Boulos Enterprises, known publicly as the husband of Tiffany Trump.
-
D.
George Boulos
George Boulos is a member of the prominent Boulos family, known for its influence and activities in business and public life.
-
E.
Émile Lahoud
Émile Lahoud is a Lebanese military officer and politician who served as President of Lebanon from 1998 to 2007.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0aff84c8190a5a6bf52adae1c9a |
completed | April 29, 2026, 6:09 a.m. |
Created at: April 17, 2026, 5:32 p.m.