Triple
T7006167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akhtar Mansour |
E162461
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mansour |
E161829
|
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: Mansour | Statement: [Akhtar Mansour, familyName, Mansour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mansour Context triple: [Akhtar Mansour, familyName, Mansour]
-
A.
Mansour
chosen
Mansour is an Arabic surname commonly borne by individuals across the Middle East and North Africa, often associated with notable figures in politics, business, and the arts.
-
B.
El Mounib
El Mounib is a district in Giza, Egypt, known for serving as a major southern transport hub on the Cairo Metro network.
-
C.
Mohandessin
Mohandessin is a prominent, upscale district in Giza, Egypt, known for its residential neighborhoods, commercial avenues, and vibrant urban life.
-
D.
Mounir
Mounir is a masculine given name of Arabic origin, commonly used in various Arabic-speaking and Muslim-majority countries.
-
E.
Mahmoud
Mahmoud is a common Arabic male given name widely used across the Middle East and Muslim-majority countries.
- 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_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc34b5a88190a793e07dd4d0018b |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a3f5a088190bd0fa2080a8fa648 |
completed | March 28, 2026, 5:42 a.m. |
Created at: March 27, 2026, 2:33 p.m.