Triple
T12128795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mersin Province |
E288878
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Erdemli
Erdemli is a coastal district and town in southern Turkey known for its Mediterranean beaches, citrus production, and nearby ancient ruins.
|
E1028143
|
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: Erdemli | Statement: [Mersin Province, hasDistrict, Erdemli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erdemli Context triple: [Mersin Province, hasDistrict, Erdemli]
-
A.
Gümüldür
Gümüldür is a coastal neighborhood and popular seaside resort area in the Menderes district of İzmir Province, Turkey.
-
B.
Bilecik
Bilecik is a small city in northwestern Turkey known as the capital of Bilecik Province and for its proximity to the historic town of Söğüt, birthplace of the Ottoman Empire.
-
C.
Ereğli
Ereğli is a district and town in central Turkey known for its agricultural production and location within Konya Province on the Central Anatolian plateau.
-
D.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
E.
Karacabey
Karacabey is a town and district in northwestern Turkey known for its agriculture and proximity to both the Marmara Sea and the city of Bursa.
- 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: Erdemli Triple: [Mersin Province, hasDistrict, Erdemli]
Generated description
Erdemli is a coastal district and town in southern Turkey known for its Mediterranean beaches, citrus production, and nearby ancient ruins.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Erdemli Target entity description: Erdemli is a coastal district and town in southern Turkey known for its Mediterranean beaches, citrus production, and nearby ancient ruins.
-
A.
Gümüldür
Gümüldür is a coastal neighborhood and popular seaside resort area in the Menderes district of İzmir Province, Turkey.
-
B.
Bilecik
Bilecik is a small city in northwestern Turkey known as the capital of Bilecik Province and for its proximity to the historic town of Söğüt, birthplace of the Ottoman Empire.
-
C.
Ereğli
Ereğli is a district and town in central Turkey known for its agricultural production and location within Konya Province on the Central Anatolian plateau.
-
D.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
E.
Karacabey
Karacabey is a town and district in northwestern Turkey known for its agriculture and proximity to both the Marmara Sea and the city of Bursa.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9158a2c2c8190aaff9d0cce177565 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6fef515488190957a69e1cc901d65 |
completed | May 3, 2026, 7:53 a.m. |
| NEDg | Description generation | batch_69f6ffeec1e8819090e1917fc6449ede |
completed | May 3, 2026, 7:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7017d8d308190bb54958764026325 |
completed | May 3, 2026, 8:04 a.m. |
Created at: April 8, 2026, 9:49 p.m.