Triple
T6383843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohamed Nasheed |
E143650
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mohamed |
E162955
|
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: Mohamed | Statement: [Mohamed Nasheed, givenName, Mohamed]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mohamed Context triple: [Mohamed Nasheed, givenName, Mohamed]
-
A.
Mohamed
chosen
Mohamed is a common Arabic male given name, widely used across the Muslim world in honor of the Prophet Muhammad.
-
B.
Mahmoud
Mahmoud is a common Arabic male given name widely used across the Middle East and Muslim-majority countries.
-
C.
Ibrahim
Ibrahim is the name used in Islamic tradition for the prophet Abraham, a central patriarchal figure revered in Judaism, Christianity, and Islam.
-
D.
Ibrahim
Ibrahim was a son of Orhan Gazi, the second ruler of the early Ottoman state.
-
E.
Ahmed
Ahmed is a common Arabic male given name meaning "most commendable" or "most praiseworthy."
- 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_69c008dac1ec81909cef8157ccd69962 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06856434481909cbbca1c12c6e070 |
completed | March 22, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c669dbb0708190b0651c524a80a251 |
completed | March 27, 2026, 11:28 a.m. |
Created at: March 22, 2026, 4:34 p.m.