Triple
T15020043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Possessor |
E378058
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Karim Hussain
Karim Hussain is a Canadian cinematographer and filmmaker known for his visually distinctive work on genre and horror films.
|
E1132909
|
NE FINISHED |
How this triple was built (4 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: Karim Hussain | Statement: [Possessor, cinematographyBy, Karim Hussain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karim Hussain Context triple: [Possessor, cinematographyBy, Karim Hussain]
-
A.
Karim Sanjabi
Karim Sanjabi was an influential Iranian nationalist politician, lawyer, and academic who became a leading figure of the National Front and a prominent opponent of the Pahlavi monarchy.
-
B.
Karim
Karim is a French professional footballer widely recognized as one of the most prolific strikers of his generation.
-
C.
Karim
Karim is the birth name of Moroccan-American rapper and producer French Montana.
-
D.
Karim
Karim is a masculine given name of Arabic origin commonly used across the Middle East, North Africa, and Muslim communities worldwide.
-
E.
Karim
Karim is a surname most prominently associated with Jawed Karim, the computer scientist and entrepreneur who co-founded YouTube.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Karim Hussain Triple: [Possessor, cinematographyBy, Karim Hussain]
Generated description
Karim Hussain is a Canadian cinematographer and filmmaker known for his visually distinctive work on genre and horror films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karim Hussain Target entity description: Karim Hussain is a Canadian cinematographer and filmmaker known for his visually distinctive work on genre and horror films.
-
A.
Karim Sanjabi
Karim Sanjabi was an influential Iranian nationalist politician, lawyer, and academic who became a leading figure of the National Front and a prominent opponent of the Pahlavi monarchy.
-
B.
Karim
Karim is a French professional footballer widely recognized as one of the most prolific strikers of his generation.
-
C.
Karim
Karim is the birth name of Moroccan-American rapper and producer French Montana.
-
D.
Karim
Karim is a masculine given name of Arabic origin commonly used across the Middle East, North Africa, and Muslim communities worldwide.
-
E.
Karim
Karim is a surname most prominently associated with Jawed Karim, the computer scientist and entrepreneur who co-founded YouTube.
- F. None of above. chosen
Provenance (5 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded76445988190984b57de66e00c4a |
completed | April 15, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dd078e481908ec78db57541fc4c |
completed | May 9, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fe9f3afcc08190bd9eac0b2619bf0a |
completed | May 9, 2026, 2:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe9fa89bd481909235d2ec377a0d8e |
completed | May 9, 2026, 2:44 a.m. |
Created at: April 10, 2026, 2:56 a.m.