Triple
T17728558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oya Baydar |
E442528
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Baydar
Baydar is a Turkish surname borne by various notable individuals, including writers, academics, and public figures.
|
E1283725
|
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: Baydar | Statement: [Oya Baydar, familyName, Baydar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baydar Context triple: [Oya Baydar, familyName, Baydar]
-
A.
Akyurt
Akyurt is a district and rapidly developing suburban area of Ankara in central Turkey, known for its industrial zones and proximity to the capital’s airport.
-
B.
Orhangazi
Orhangazi is a town and district in northwestern Turkey known for its olive cultivation and location near Lake İznik in Bursa Province.
-
C.
Dursunbey
Dursunbey is a town and district in western Turkey known for its forestry, timber production, and rural character within Balıkesir Province.
-
D.
Kaynarca
Kaynarca is a small town and district in northwestern Turkey, located within Sakarya Province and known for its rural character and agricultural activities.
-
E.
Beylikova
Beylikova is a small town and district in central Turkey known for its agricultural activities and location within Eskişehir Province.
- 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: Baydar Triple: [Oya Baydar, familyName, Baydar]
Generated description
Baydar is a Turkish surname borne by various notable individuals, including writers, academics, and public figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baydar Target entity description: Baydar is a Turkish surname borne by various notable individuals, including writers, academics, and public figures.
-
A.
Akyurt
Akyurt is a district and rapidly developing suburban area of Ankara in central Turkey, known for its industrial zones and proximity to the capital’s airport.
-
B.
Orhangazi
Orhangazi is a town and district in northwestern Turkey known for its olive cultivation and location near Lake İznik in Bursa Province.
-
C.
Dursunbey
Dursunbey is a town and district in western Turkey known for its forestry, timber production, and rural character within Balıkesir Province.
-
D.
Kaynarca
Kaynarca is a small town and district in northwestern Turkey, located within Sakarya Province and known for its rural character and agricultural activities.
-
E.
Beylikova
Beylikova is a small town and district in central Turkey known for its agricultural activities and location within Eskişehir Province.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e478e4ae5c8190a6f0743f7e74b5bf |
completed | April 19, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a023034858881908c09acc78839e5d9 |
completed | May 11, 2026, 7:38 p.m. |
| NEDg | Description generation | batch_6a0230f2f4c88190ab54ae494c63e223 |
completed | May 11, 2026, 7:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0231667fd481908663a447670a9a0e |
completed | May 11, 2026, 7:43 p.m. |
Created at: April 10, 2026, 10:08 a.m.