Triple
T5548570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahmoud |
E145469
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Mahmoud |
E145469
|
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: Mahmoud | Statement: [Mahmoud, hasVariant, Mahmoud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahmoud Context triple: [Mahmoud, hasVariant, Mahmoud]
-
A.
Mahmoud
chosen
Mahmoud is a common Arabic male given name widely used across the Middle East and Muslim-majority countries.
-
B.
Mohamed
Mohamed is a common Arabic male given name, widely used across the Muslim world in honor of the Prophet Muhammad.
-
C.
Hamed
Hamed is a masculine given name commonly used in Arabic-speaking and Muslim-majority cultures.
-
D.
Fayez
Fayez is an Arabic male given name commonly used in the Middle East and North Africa, meaning "victorious" or "successful."
-
E.
Omar
Omar is a masculine given name of Arabic origin meaning "flourishing" or "long-lived," borne by numerous historical and contemporary figures worldwide.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe143ec8190bb67d2530c92a419 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c059e39b7c81908c5eb3e940366562 |
completed | March 22, 2026, 9:06 p.m. |
Created at: March 22, 2026, 3:35 p.m.