Triple
T17287699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mediterranean Region |
E419701
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Kahramanmaraş |
—
|
NE NERFINISHED |
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: Kahramanmaraş | Statement: [Mediterranean Region, contains, Kahramanmaraş]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kahramanmaraş Context triple: [Mediterranean Region, contains, Kahramanmaraş]
-
A.
Gaziantep
Gaziantep is a major city in southeastern Turkey known for its rich history, cultural heritage, and renowned pistachio-based cuisine, especially baklava.
-
B.
Kütahya
Kütahya is a historic city in western Turkey known for its Ottoman-era architecture and traditional ceramic and tile production.
-
C.
Kahramanmaraş Province
chosen
Kahramanmaraş Province is an administrative region in southern Turkey known for its historic city of Kahramanmaraş and its famous Maraş ice cream.
-
D.
Kilis
Kilis is a small Turkish city near the Syrian border known for its strategic location, cross-border trade, and distinctive regional cuisine.
-
E.
Diyarbekir
Diyarbekir is a historic city in southeastern Turkey, widely known today as Diyarbakır and notable for its ancient basalt city walls and rich Kurdish and Ottoman heritage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e43780fad88190b82193c8335e2f11 |
completed | April 19, 2026, 2:01 a.m. |
Created at: April 10, 2026, 5:40 a.m.