Triple
T3851617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | early Ottoman period |
E85306
|
entity |
| Predicate | hasKeyRuler |
P810
|
FINISHED |
| Object | Orhan |
E19924
|
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: Orhan | Statement: [early Ottoman period, hasKeyRuler, Orhan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orhan Context triple: [early Ottoman period, hasKeyRuler, Orhan]
-
A.
Orhan
chosen
Orhan was the second ruler of the early Ottoman state who significantly expanded its territories in northwestern Anatolia and laid foundations for its future imperial structure.
-
B.
Orhan Arda
Orhan Arda was a Turkish architect best known as one of the designers of Anıtkabir, the mausoleum of Mustafa Kemal Atatürk in Ankara.
-
C.
Ahmet
Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
-
D.
Eyüp
Eyüp is a historic district on Istanbul’s Golden Horn, known for its important Ottoman-era mosque complex and traditional neighborhoods.
-
E.
Mehmet
Mehmet is a common Turkish male given name of Arabic origin, widely used across Turkey and among Turkish communities.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebd0feb081909cc1d5bf41e4acd6 |
completed | March 9, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b50419e7a0819087f9bc7fbfec4116 |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:19 p.m.