Triple
T12967161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muğla Province |
E321290
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Seydikemer
Seydikemer is a rural district and town in southwestern Turkey known for its agricultural landscape and proximity to popular coastal and historical sites in Muğla Province.
|
E1079157
|
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: Seydikemer | Statement: [Muğla Province, contains, Seydikemer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seydikemer Context triple: [Muğla Province, contains, Seydikemer]
-
A.
Suşehri
Suşehri is a town and district in northeastern Turkey known for its location within Sivas Province and its surrounding mountainous landscape.
-
B.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
C.
Güzelyurt
Güzelyurt is a historic town in Turkey’s Cappadocia region, known for its rock-cut churches, underground cities, and scenic valleys.
-
D.
Karataş
Karataş is a coastal town and district in Adana Province, southern Turkey, known for its fishing, agriculture, and Mediterranean beaches.
-
E.
Gümüldür
Gümüldür is a coastal neighborhood and popular seaside resort area in the Menderes district of İzmir Province, Turkey.
- 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: Seydikemer Triple: [Muğla Province, contains, Seydikemer]
Generated description
Seydikemer is a rural district and town in southwestern Turkey known for its agricultural landscape and proximity to popular coastal and historical sites in Muğla Province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seydikemer Target entity description: Seydikemer is a rural district and town in southwestern Turkey known for its agricultural landscape and proximity to popular coastal and historical sites in Muğla Province.
-
A.
Suşehri
Suşehri is a town and district in northeastern Turkey known for its location within Sivas Province and its surrounding mountainous landscape.
-
B.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
C.
Güzelyurt
Güzelyurt is a historic town in Turkey’s Cappadocia region, known for its rock-cut churches, underground cities, and scenic valleys.
-
D.
Karataş
Karataş is a coastal town and district in Adana Province, southern Turkey, known for its fishing, agriculture, and Mediterranean beaches.
-
E.
Gümüldür
Gümüldür is a coastal neighborhood and popular seaside resort area in the Menderes district of İzmir Province, Turkey.
- 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e3f702481908f0f90f4f12d3f4d |
completed | April 10, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd084d94081909ae911fce5640aaf |
completed | May 7, 2026, 5:48 p.m. |
| NEDg | Description generation | batch_69fcd21a2a408190ab335e99fcbbd9ae |
completed | May 7, 2026, 5:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fcd2e1b2ec81909caab1bfc6394258 |
completed | May 7, 2026, 5:58 p.m. |
Created at: April 9, 2026, 8:30 p.m.