Triple
T5572557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avşa Island |
E146236
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Avşa
Avşa is a small coastal settlement on Avşa Island in Turkey, known for its beaches and tourism.
|
E531003
|
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: Avşa | Statement: [Avşa Island, hasSettlement, Avşa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avşa Context triple: [Avşa Island, hasSettlement, Avşa]
-
A.
Ayvalık
Ayvalık is a coastal town in northwestern Turkey known for its historic Greek architecture, olive oil production, and scenic Aegean Sea views.
-
B.
Aliağa
Aliağa is a coastal industrial district and port town in İzmir Province, Turkey, known for its petrochemical facilities and ship-breaking yards.
-
C.
Darıca
Darıca is a coastal town and district in northwestern Turkey, situated on the Sea of Marmara and known for its zoo, recreation areas, and proximity to Istanbul.
-
D.
Akyurt
Akyurt is a district and rapidly developing suburban area of Ankara in central Turkey, known for its industrial zones and proximity to the capital’s airport.
-
E.
Orlu
Orlu is a prominent town and commercial hub in southeastern Nigeria that serves as an important center for trade, industry, and regional administration.
- 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: Avşa Triple: [Avşa Island, hasSettlement, Avşa]
Generated description
Avşa is a small coastal settlement on Avşa Island in Turkey, known for its beaches and tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Avşa Target entity description: Avşa is a small coastal settlement on Avşa Island in Turkey, known for its beaches and tourism.
-
A.
Ayvalık
Ayvalık is a coastal town in northwestern Turkey known for its historic Greek architecture, olive oil production, and scenic Aegean Sea views.
-
B.
Aliağa
Aliağa is a coastal industrial district and port town in İzmir Province, Turkey, known for its petrochemical facilities and ship-breaking yards.
-
C.
Darıca
Darıca is a coastal town and district in northwestern Turkey, situated on the Sea of Marmara and known for its zoo, recreation areas, and proximity to Istanbul.
-
D.
Akyurt
Akyurt is a district and rapidly developing suburban area of Ankara in central Turkey, known for its industrial zones and proximity to the capital’s airport.
-
E.
Orlu
Orlu is a prominent town and commercial hub in southeastern Nigeria that serves as an important center for trade, industry, and regional administration.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020518f348190879ac67dab307134 |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0284ef6e48190bae9c9a1b1d77f5d |
completed | March 22, 2026, 5:35 p.m. |
| NEDg | Description generation | batch_69c037b5be3c819098c8500350267a1e |
completed | March 22, 2026, 6:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0393144248190a97d1f82b81cc868 |
completed | March 22, 2026, 6:47 p.m. |
Created at: March 22, 2026, 3:37 p.m.