Triple
T22526986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | نهر الحب |
E556932
|
entity |
| Predicate | بطولة |
P148739
|
FINISHED |
| Object | فردوس محمد |
—
|
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: فردوس محمد | Statement: [نهر الحب, بطولة, فردوس محمد]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: فردوس محمد Context triple: [نهر الحب, بطولة, فردوس محمد]
-
A.
فردوس محمد
chosen
فردوس محمد ممثلة مصرية شاركت في عدد من الأفلام والمسرحيات، وعُرفت بأدوارها الثانوية المميزة في السينما المصرية الكلاسيكية.
-
B.
Fazlollah
Fazlollah is a Persian given name notably borne by Iranian general and politician Fazlollah Zahedi, a key figure in Iran’s mid-20th-century history.
-
C.
Sadeq
Sadeq is a Persian given name commonly used for males in Iran and other Persian-speaking communities.
-
D.
Mohammad Reza Isfahani
Mohammad Reza Isfahani was a prominent Safavid-era Iranian architect best known for designing masterpieces of Isfahan’s royal square, including the celebrated Sheikh Lotfollah Mosque.
-
E.
Hossain Emadeddin
Hossain Emadeddin was an Iranian non-professional actor best known for his acclaimed leading role in Jafar Panahi’s film "Crimson Gold."
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed411488190a51320930b9805c2 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 16, 2026, 8:51 p.m.