Triple
T21051151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jawad |
E518584
|
entity |
| Predicate | alternativeTransliteration |
P5923
|
FINISHED |
| Object | Jawwad |
—
|
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: Jawwad | Statement: [Jawad, alternativeTransliteration, Jawwad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jawwad Context triple: [Jawad, alternativeTransliteration, Jawwad]
-
A.
Jawad
chosen
Jawad is a masculine given name of Arabic origin commonly used across the Middle East and Muslim-majority regions.
-
B.
Bilall
Bilall is a Belgian film director and screenwriter best known as one half of the directing duo Adil & Bilall, recognized for stylish action and crime films like "Bad Boys for Life."
-
C.
Asif
Asif is a common male given name used in South Asian and Middle Eastern cultures, notably borne by Pakistani politician Asif Ali Zardari.
-
D.
Sajid
Sajid is a masculine given name of Arabic origin commonly used in South Asian and Muslim communities.
-
E.
Walid Nadeem
Walid Nadeem is a fictional character known primarily as the romantic partner of Frank Bledsoe in the film "Uncle Frank."
- 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7bd96c81909cb46419ad4e1222 |
completed | April 21, 2026, 4:30 a.m. |
Created at: April 16, 2026, 2:35 p.m.