Triple
T6045420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Süleyman Pasha |
E134654
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Süleyman |
E258149
|
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: Süleyman | Statement: [Süleyman Pasha, givenName, Süleyman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Süleyman Context triple: [Süleyman Pasha, givenName, Süleyman]
-
A.
Suleyman
chosen
Suleyman is a surname most prominently associated with Mustafa Suleyman, a British artificial intelligence entrepreneur and co-founder of DeepMind.
-
B.
Süleyman Çelebi
Süleyman Çelebi was an early 15th-century Ottoman prince who ruled parts of Anatolia and Rumelia during the Ottoman Interregnum following the defeat of his father Bayezid I.
-
C.
Suleiman
Suleiman was an 11th-century Seljuk prince and founder of the Sultanate of Rum in Anatolia.
-
D.
Selim
Selim is the passionate and ill-fated protagonist of Lord Byron’s narrative poem "The Bride of Abydos."
-
E.
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.
- 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056e41f98819089c205ba6138faf0 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c6a0fdc8190be37008d4f036e51 |
completed | March 28, 2026, 9:16 a.m. |
Created at: March 22, 2026, 4:09 p.m.