Triple
T15828956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bamsi Beyrek Boyu |
E383817
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Bamsi Beyrek
Bamsi Beyrek is a legendary hero of the Oghuz Turkic epic tradition, celebrated for his bravery, loyalty, and romantic exploits in the Book of Dede Korkut.
|
E1178972
|
NE FINISHED |
How this triple was built (4 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: Bamsi Beyrek | Statement: [Bamsi Beyrek Boyu, mainCharacter, Bamsi Beyrek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bamsi Beyrek Context triple: [Bamsi Beyrek Boyu, mainCharacter, Bamsi Beyrek]
-
A.
Bekir
Bekir is a common Turkish male given name of Arabic origin, often associated with early Islamic history and frequently borne by notable figures in Turkey.
-
B.
Sadi Irmak
Sadi Irmak was a Turkish physician, academic, and politician who briefly served as Prime Minister of Turkey in the mid-1970s.
-
C.
Güntekin
Güntekin is the surname of the renowned Turkish novelist and playwright Reşat Nuri, best known for works such as "Çalıkuşu."
-
D.
Ahmetbeyli
Ahmetbeyli is a coastal neighborhood and historical area in western Turkey known for its beaches and proximity to ancient ruins.
-
E.
Celal
Celal is a central character in Orhan Pamuk’s novel "The Black Book," around whom much of the story’s mystery and identity exploration revolves.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bamsi Beyrek Triple: [Bamsi Beyrek Boyu, mainCharacter, Bamsi Beyrek]
Generated description
Bamsi Beyrek is a legendary hero of the Oghuz Turkic epic tradition, celebrated for his bravery, loyalty, and romantic exploits in the Book of Dede Korkut.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bamsi Beyrek Target entity description: Bamsi Beyrek is a legendary hero of the Oghuz Turkic epic tradition, celebrated for his bravery, loyalty, and romantic exploits in the Book of Dede Korkut.
-
A.
Bekir
Bekir is a common Turkish male given name of Arabic origin, often associated with early Islamic history and frequently borne by notable figures in Turkey.
-
B.
Sadi Irmak
Sadi Irmak was a Turkish physician, academic, and politician who briefly served as Prime Minister of Turkey in the mid-1970s.
-
C.
Güntekin
Güntekin is the surname of the renowned Turkish novelist and playwright Reşat Nuri, best known for works such as "Çalıkuşu."
-
D.
Ahmetbeyli
Ahmetbeyli is a coastal neighborhood and historical area in western Turkey known for its beaches and proximity to ancient ruins.
-
E.
Celal
Celal is a central character in Orhan Pamuk’s novel "The Black Book," around whom much of the story’s mystery and identity exploration revolves.
- F. None of above. chosen
Provenance (5 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e11e62aba8819090978801f4df73fe |
completed | April 16, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff999f9ccc8190bc859c2b78a16baf |
completed | May 9, 2026, 8:31 p.m. |
| NEDg | Description generation | batch_69ff9bf7363c8190a65798028305b1da |
completed | May 9, 2026, 8:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff9c580d608190a7b3de11a924cba7 |
completed | May 9, 2026, 8:43 p.m. |
Created at: April 10, 2026, 4:49 a.m.