Triple
T18910104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aml Ameen |
E462579
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Ameen |
—
|
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: Ameen | Statement: [Aml Ameen, familyName, Ameen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ameen Context triple: [Aml Ameen, familyName, Ameen]
-
A.
Aml Ameen
chosen
Aml Ameen is a British actor known for roles in films like "Kidulthood" and "The Maze Runner" as well as television series such as "Sense8."
-
B.
Al-Ameed
Al-Ameed is a popular nickname for Al Ittihad Club, one of Saudi Arabia’s oldest and most successful football teams.
-
C.
Amin
Amin is a given name notably borne by Haj Amin al-Husseini, the controversial Palestinian Arab nationalist and Muslim leader active in the early to mid-20th century.
-
D.
Tahsin
Tahsin is a masculine given name of Turkish and Arabic origin, commonly used in Turkey and other Muslim-majority countries.
-
E.
Aamer
Aamer is a male given name of Arabic origin, often used in Muslim communities and sometimes transliterated as Amer.
- 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c62182f48190ad81b6ef0c7bc7da |
completed | April 20, 2026, 6:22 a.m. |
Created at: April 10, 2026, 11:58 a.m.