Triple
T229862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amr Moussa |
E4387
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Amr
Amr is a common Arabic male given name, often associated with historical and contemporary figures across the Arab world.
|
E30384
|
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: Amr | Statement: [Amr Moussa, givenName, Amr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amr Context triple: [Amr Moussa, givenName, Amr]
-
A.
Ahmed
Ahmed is a common Arabic male given name meaning "most commendable" or "most praiseworthy."
-
B.
Entissar Amer
Entissar Amer is the First Lady of Egypt and the wife of President Abdel Fattah el-Sisi.
-
C.
Nazlet El-Semman
Nazlet El-Semman is a village on the outskirts of Giza in Egypt, best known as the primary gateway settlement to the Giza Pyramids and Sphinx plateau.
-
D.
As-Samad
As-Samad is one of the names of Allah in Islam, signifying the One who is absolutely self-sufficient, eternally depended upon by all creation, and free of all need.
-
E.
Hassan Aref
Hassan Aref was a prominent physicist and engineer known for his pioneering contributions to fluid dynamics, particularly in vortex dynamics and chaotic advection.
- 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: Amr Triple: [Amr Moussa, givenName, Amr]
Generated description
Amr is a common Arabic male given name, often associated with historical and contemporary figures across the Arab world.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Amr Target entity description: Amr is a common Arabic male given name, often associated with historical and contemporary figures across the Arab world.
-
A.
Ahmed
Ahmed is a common Arabic male given name meaning "most commendable" or "most praiseworthy."
-
B.
Entissar Amer
Entissar Amer is the First Lady of Egypt and the wife of President Abdel Fattah el-Sisi.
-
C.
Nazlet El-Semman
Nazlet El-Semman is a village on the outskirts of Giza in Egypt, best known as the primary gateway settlement to the Giza Pyramids and Sphinx plateau.
-
D.
As-Samad
As-Samad is one of the names of Allah in Islam, signifying the One who is absolutely self-sufficient, eternally depended upon by all creation, and free of all need.
-
E.
Hassan Aref
Hassan Aref was a prominent physicist and engineer known for his pioneering contributions to fluid dynamics, particularly in vortex dynamics and chaotic advection.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25cac7994819080b0b3b10808f8e5 |
completed | Feb. 28, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3673257f081908bcb84cbedef3c07 |
completed | Feb. 28, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69a367b28e6c819082ad23cad05c5071 |
completed | Feb. 28, 2026, 10:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3683fafec8190b46278c7309fe577 |
completed | Feb. 28, 2026, 10:12 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.