Triple
T18805852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laith Nakli |
E459870
|
entity |
| Predicate | notableRole |
P22
|
FINISHED |
| Object | Uncle Naseem |
—
|
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: Uncle Naseem | Statement: [Laith Nakli, notableRole, Uncle Naseem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uncle Naseem Context triple: [Laith Nakli, notableRole, Uncle Naseem]
-
A.
Uncle Naseem
chosen
Uncle Naseem is a fictional character portrayed by actor Laith Nakli, known as a gruff yet caring Syrian uncle in the TV series "Ramy."
-
B.
Uncle Aziz
Uncle Aziz is the central figure in the story "Paradise," around whom the narrative’s themes and events primarily revolve.
-
C.
Uncle Reem
Uncle Reem is a minor fictional character in the "Coming to America" universe, known primarily as a relative of Prince Akeem Joffer.
-
D.
Alm-Uncle
Alm-Uncle is the reclusive, elderly grandfather of Heidi in Johanna Spyri’s classic Swiss children’s novel, known for his gruff exterior and deep, ultimately loving bond with his granddaughter.
-
E.
Najeeb
Najeeb is a masculine given name of Arabic origin meaning "noble" or "distinguished."
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3d6d5e081909d8285e52cb753ba |
completed | April 20, 2026, 3:56 a.m. |
Created at: April 10, 2026, 11:53 a.m.