Triple
T8306960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahmoud Zahar |
E194486
|
entity |
| Predicate | givenName |
P17
|
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 Zahar, givenName, Mahmoud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahmoud Context triple: [Mahmoud Zahar, givenName, 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.
Naser
Naser is a masculine given name of Arabic origin, commonly used across the Middle East and Muslim-majority regions, meaning "helper" or "victorious."
-
D.
Hamed
Hamed is a masculine given name commonly used in Arabic-speaking and Muslim-majority cultures.
-
E.
Ahmad
Ahmad is the narrator of the film "Soul Food," providing the story’s perspective and emotional throughline.
- 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_69ca82e613e88190bf8139669bbd0d53 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f2a86bc81909749c40c640aa9f8 |
completed | March 31, 2026, 8 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd955100448190862fd52d660585fd |
completed | April 1, 2026, 9:59 p.m. |
Created at: March 30, 2026, 5:54 p.m.