Triple
T11177586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarsus River |
E264450
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object | Mersin |
E288878
|
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: Mersin | Statement: [Tarsus River, nearCity, Mersin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mersin Context triple: [Tarsus River, nearCity, Mersin]
-
A.
Antakya
Antakya is a city in southern Turkey, historically known as Antioch, renowned as an important center of Hellenistic, Roman, and early Christian civilization.
-
B.
Mersin Province
chosen
Mersin Province is a coastal region in southern Turkey on the Mediterranean Sea, known for its major port city of Mersin and its rich historical and agricultural significance.
-
C.
Samsun
Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
-
D.
Burdur
Burdur is a city in southwestern Turkey known for its nearby lakes, archaeological sites, and traditional Ottoman-era architecture.
-
E.
Gaziantep
Gaziantep is a major city in southeastern Turkey known for its rich history, cultural heritage, and renowned pistachio-based cuisine, especially baklava.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8987e1081909b28a0bdb866beae |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4acf79b748190b117355f60c8c015 |
completed | April 19, 2026, 10:22 a.m. |
Created at: April 8, 2026, 9:29 p.m.