Triple
T15976273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alanyaspor |
E387455
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Alanya |
E429092
|
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: Alanya | Statement: [Alanyaspor, location, Alanya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alanya Context triple: [Alanyaspor, location, Alanya]
-
A.
Alanya
chosen
Alanya is a popular Mediterranean resort city in southern Turkey, known for its beaches, historic castle, and role as a major tourism hub.
-
B.
Antalya
Antalya is a major resort city on Turkey’s Mediterranean coast, known for its beaches, historic old town, and role as a gateway to the Turkish Riviera.
-
C.
Fethiye
Fethiye is a popular coastal resort city in southwestern Turkey known for its natural harbor, nearby Ölüdeniz lagoon, and proximity to ancient Lycian sites.
-
D.
Marmaris
Marmaris is a popular Turkish coastal resort city known for its beaches, marinas, and vibrant nightlife along the Mediterranean.
-
E.
Bodrum
Bodrum is a popular coastal city and resort town in southwestern Turkey, known for its beaches, nightlife, and historic landmarks such as Bodrum Castle.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1575166d081909c5275c235c8ce0f |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbc6f4c08190b816bf6d92114ad2 |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:54 a.m.