Triple
T20132879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mehmed Selim |
E490941
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Selim |
—
|
NE NERFINISHED |
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: Selim | Statement: [Mehmed Selim, givenName, Selim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Selim Context triple: [Mehmed Selim, givenName, Selim]
-
A.
Selim
chosen
Selim is the passionate and ill-fated protagonist of Lord Byron’s narrative poem "The Bride of Abydos."
-
B.
Suleiman
Suleiman was an 11th-century Seljuk prince and founder of the Sultanate of Rum in Anatolia.
-
C.
Selim I
Selim I was a 16th-century Ottoman sultan who dramatically expanded the empire by conquering the Mamluk Sultanate and bringing the holy cities of Mecca and Medina under Ottoman control.
-
D.
Suleyman
Suleyman is a surname most prominently associated with Mustafa Suleyman, a British artificial intelligence entrepreneur and co-founder of DeepMind.
-
E.
Süleyman
Süleyman is a Turkish masculine given name most famously borne by Süleyman Demirel, a long-serving prime minister and president of Turkey.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66763ee908190af64af31b4ca2377 |
completed | April 20, 2026, 5:50 p.m. |
Created at: April 11, 2026, 11:32 p.m.