Triple
T7075928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mansour Bahy |
E164817
|
entity |
| Predicate | originalWorkTitle |
P6930
|
FINISHED |
| Object | ميرامار |
E150000
|
NE 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: ميرامار | Statement: [Mansour Bahy, originalWorkTitle, ميرامار]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ميرامار Context triple: [Mansour Bahy, originalWorkTitle, ميرامار]
-
A.
ميرامار
chosen
"ميرامار" هي رواية عربية شهيرة لنجيب محفوظ تدور أحداثها في بنسيون بالإسكندرية وتستعرض تحولات المجتمع المصري في ستينيات القرن العشرين من خلال وجهات نظر متعددة.
-
B.
Ramiro
Ramiro is a masculine given name of Spanish and Portuguese origin, historically borne by several medieval kings and nobles in the Iberian Peninsula.
-
C.
Guillermo
Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
-
D.
Alcaufar
Alcaufar is a small coastal village and beach resort on the southeastern coast of Menorca in Spain, known for its sheltered bay and tranquil atmosphere.
-
E.
Ataulfo
Ataulfo is a small, golden-yellow, sweet and creamy Mexican mango variety prized for its smooth, fiberless flesh.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6887cbc6c8190bdfac42d940f4d8a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4ce3d3c81908cbb912b256aadbf |
completed | March 27, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79468c7688190bf10433f05e77574 |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:40 p.m.