Triple
T8428787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sasha Piqué Mebarak |
E199067
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Sasha Piqué Mebarak |
E199067
|
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: Sasha Piqué Mebarak | Statement: [Sasha Piqué Mebarak, fullName, Sasha Piqué Mebarak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sasha Piqué Mebarak Context triple: [Sasha Piqué Mebarak, fullName, Sasha Piqué Mebarak]
-
A.
Sasha Piqué Mebarak
chosen
Sasha Piqué Mebarak is the younger son of Colombian singer Shakira and Spanish footballer Gerard Piqué.
-
B.
Sara Sikka
Sara Sikka is an alternative name for the Sika language, an Austronesian language spoken primarily on Flores Island in Indonesia.
-
C.
Sasha Barrese
Sasha Barrese is an American actress best known for playing Doug’s fiancée Tracy in the comedy film "The Hangover" and its sequels.
-
D.
Alexis Mdivani
Alexis Mdivani was a Georgian-born aristocrat and member of the socially prominent "Marrying Mdivanis," known for his high-profile marriage into great wealth and status.
-
E.
Mimi Chakib
Mimi Chakib was a prominent Egyptian film and stage actress known for her strong supporting roles in classic mid-20th-century Arabic cinema.
- 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbd125a53c8190b83a4f6148baa779 |
completed | March 31, 2026, 1:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d5a671c8190aebbe94e8838cddb |
completed | April 2, 2026, 7:40 a.m. |
Created at: March 30, 2026, 6:07 p.m.