Triple
T5491962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asian Turkey |
E123721
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Gümüşhane
Gümüşhane is a small city in northeastern Turkey known for its mountainous landscape, mining history, and traditional stone architecture.
|
E595406
|
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: Gümüşhane | Statement: [Asian Turkey, containsCity, Gümüşhane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gümüşhane Context triple: [Asian Turkey, containsCity, Gümüşhane]
-
A.
Kalecik
Kalecik is a district and town in central Turkey known for its historic architecture and the locally famous Kalecik Karası grape variety.
-
B.
Keçiören
Keçiören is a densely populated metropolitan district and municipality of Ankara, known as one of the capital city’s major residential and commercial areas.
-
C.
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.
-
D.
Doğanhisar
Doğanhisar is a rural district and town in central Turkey known for its agricultural economy and location within the Konya region.
-
E.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
- 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: Gümüşhane Triple: [Asian Turkey, containsCity, Gümüşhane]
Generated description
Gümüşhane is a small city in northeastern Turkey known for its mountainous landscape, mining history, and traditional stone architecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gümüşhane Target entity description: Gümüşhane is a small city in northeastern Turkey known for its mountainous landscape, mining history, and traditional stone architecture.
-
A.
Kalecik
Kalecik is a district and town in central Turkey known for its historic architecture and the locally famous Kalecik Karası grape variety.
-
B.
Keçiören
Keçiören is a densely populated metropolitan district and municipality of Ankara, known as one of the capital city’s major residential and commercial areas.
-
C.
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.
-
D.
Doğanhisar
Doğanhisar is a rural district and town in central Turkey known for its agricultural economy and location within the Konya region.
-
E.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9280403c8190baaa3f7923449a37 |
completed | March 20, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6536fc20c81909b6c57d559880877 |
completed | March 27, 2026, 9:52 a.m. |
| NEDg | Description generation | batch_69c6541014d88190a80baa7f5e94a7d8 |
completed | March 27, 2026, 9:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c655140fbc8190ab8248a9e0c3de71 |
completed | March 27, 2026, 9:59 a.m. |
Created at: March 20, 2026, 2:10 p.m.