Triple
T7087238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Süleyman Demirel |
E165105
|
entity |
| Predicate | burialPlace |
P196
|
FINISHED |
| Object | İslamköy |
E639970
|
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: İslamköy | Statement: [Süleyman Demirel, burialPlace, İslamköy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: İslamköy Context triple: [Süleyman Demirel, burialPlace, İslamköy]
-
A.
İslamköy
chosen
İslamköy is a village in Turkey best known as the birthplace of former Turkish president and prime minister Süleyman Demirel.
-
B.
Poyrazköy
Poyrazköy is a coastal neighborhood on the Asian side of Istanbul, Turkey, situated at the northern entrance of the Bosphorus Strait.
-
C.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
-
D.
Şirinköy
Şirinköy is a village located on Gökçeada, Turkey’s largest Aegean island in the Çanakkale Province.
-
E.
Nallıhan
Nallıhan is a district and town in Turkey known for its natural landscapes, including colorful rock formations and rich birdlife, located within Ankara Province.
- 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e513d9b08190a8a8d213c2264ce4 |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c924ac88190a237d2e0ac505d51 |
completed | March 28, 2026, 9:17 a.m. |
Created at: March 27, 2026, 2:41 p.m.