Triple
T2837463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | İZBAN |
E62384
|
entity |
| Predicate | regionServed |
P82
|
FINISHED |
| Object |
Aliağa
Aliağa is a coastal industrial district and port town in İzmir Province, Turkey, known for its petrochemical facilities and ship-breaking yards.
|
E309020
|
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: Aliağa | Statement: [İZBAN, regionServed, Aliağa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aliağa Context triple: [İZBAN, regionServed, Aliağa]
-
A.
Orlu
Orlu is a prominent town and commercial hub in southeastern Nigeria that serves as an important center for trade, industry, and regional administration.
-
B.
Balçova
Balçova is a coastal district of İzmir, Turkey, known for its thermal springs, residential areas, and proximity to the city center.
-
C.
Arnavutköy
Arnavutköy is a district on the European side of Istanbul, Turkey, known for its rapidly developing urban areas and hosting the city’s main international airport.
-
D.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
-
E.
Kaymaklı
Kaymaklı is an ancient multi-level underground city in Turkey’s Cappadocia region, renowned for its extensive tunnels, living quarters, and historical use as a refuge.
- 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: Aliağa Triple: [İZBAN, regionServed, Aliağa]
Generated description
Aliağa is a coastal industrial district and port town in İzmir Province, Turkey, known for its petrochemical facilities and ship-breaking yards.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aliağa Target entity description: Aliağa is a coastal industrial district and port town in İzmir Province, Turkey, known for its petrochemical facilities and ship-breaking yards.
-
A.
Orlu
Orlu is a prominent town and commercial hub in southeastern Nigeria that serves as an important center for trade, industry, and regional administration.
-
B.
Balçova
Balçova is a coastal district of İzmir, Turkey, known for its thermal springs, residential areas, and proximity to the city center.
-
C.
Arnavutköy
Arnavutköy is a district on the European side of Istanbul, Turkey, known for its rapidly developing urban areas and hosting the city’s main international airport.
-
D.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
-
E.
Kaymaklı
Kaymaklı is an ancient multi-level underground city in Turkey’s Cappadocia region, renowned for its extensive tunnels, living quarters, and historical use as a refuge.
- 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdeede0488190a9782f55b57559ee |
completed | March 7, 2026, 8:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b055d3dbb8819094df5e6751dd96c4 |
completed | March 10, 2026, 5:33 p.m. |
| NEDg | Description generation | batch_69b05dc976848190933a988263ef1e40 |
completed | March 10, 2026, 6:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b061a2b8b48190ba01866a11a0b0c5 |
completed | March 10, 2026, 6:23 p.m. |
Created at: March 6, 2026, 10:01 p.m.