Triple
T16376540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Didim |
E397692
|
entity |
| Predicate | locatedSouthOf |
P9676
|
FINISHED |
| Object | Kuşadası |
E410825
|
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: Kuşadası | Statement: [Didim, locatedSouthOf, Kuşadası]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kuşadası Context triple: [Didim, locatedSouthOf, Kuşadası]
-
A.
Kuşadası
chosen
Kuşadası is a popular Aegean coastal resort town in western Turkey, known for its beaches, cruise port, and proximity to the ancient city of Ephesus.
-
B.
Kekova
Kekova is a small Turkish Mediterranean island and surrounding region famed for its submerged ancient ruins and scenic coastal landscape.
-
C.
Çamlıyayla
Çamlıyayla is a mountainous district and town in southern Turkey known for its cool highland climate and natural scenery.
-
D.
Kuruçeşme
Kuruçeşme is a Bosphorus-side neighborhood in Istanbul known for its waterfront parks, nightlife venues, and views of the strait.
-
E.
Köyceğiz
Köyceğiz is a town and district in southwestern Turkey known for its large lake, natural beauty, and proximity to popular Aegean and Mediterranean coastal areas.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e319d8a40c8190af37e7ed60b9c4dd |
completed | April 18, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00356406208190a9cedc1de2ab4e07 |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.