Triple
T22527259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | حسن الإمام |
E556938
|
entity |
| Predicate | مصدر_الشهرة |
P112499
|
FINISHED |
| Object | النجاح الجماهيري الواسع لأفلامه |
—
|
LITERAL 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: النجاح الجماهيري الواسع لأفلامه | Statement: [حسن الإمام, مصدر_الشهرة, النجاح الجماهيري الواسع لأفلامه]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: مصدر_الشهرة Context triple: [حسن الإمام, مصدر_الشهرة, النجاح الجماهيري الواسع لأفلامه]
-
A.
fameStatus
Indicates the level or state of public recognition or renown associated with an entity.
-
B.
fameFor
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
C.
starMadeFamous
chosen
Indicates that one entity (such as a work, event, or role) is what caused another entity (typically a person) to become widely known or famous.
-
D.
knownPrimarilyThrough
Indicates that one entity is chiefly recognized, identified, or made familiar to others by means of another entity (such as a work, role, medium, or context).
-
E.
famePeak
Indicates the time or point at which an entity reaches its highest level of fame or public recognition.
- F. None of above.
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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed411488190a51320930b9805c2 |
completed | April 29, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69e898c864148190a3f5feec7967d49c |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:51 p.m.