Triple
T6632908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahmoud Riad |
E149969
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Riad |
E492227
|
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: Riad | Statement: [Mahmoud Riad, familyName, Riad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Riad Context triple: [Mahmoud Riad, familyName, Riad]
-
A.
Riad
chosen
Riad is a masculine given name commonly used in Arabic-speaking countries, often meaning "gardens" or "meadows."
-
B.
Riad al-Asaad
Riad al-Asaad is a Syrian military defector who became a prominent opposition figure by helping lead the armed rebellion against Bashar al-Assad’s government.
-
C.
Tajrish
Tajrish is a historic and bustling neighborhood in northern Tehran known for its traditional bazaar, central square, and proximity to the Alborz Mountains.
-
D.
Al Quoz
Al Quoz is an industrial and residential district in western Dubai known for its warehouses, factories, and growing arts and cultural scene.
-
E.
Farshut
Farshut is a town in Upper Egypt known as an agricultural and local commercial center within the Qena region.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6afc9138c81909d228ce4936d6b8b |
completed | March 27, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbf329f08190a3f29c4d4c6aa136 |
completed | March 27, 2026, 6:26 p.m. |
Created at: March 27, 2026, 1:59 p.m.