Triple
T2837433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | İzmir Metro |
E62383
|
entity |
| Predicate | hasKeyStation |
P22144
|
FINISHED |
| Object |
Evka-3 station
Evka-3 station is a major terminal stop on the İzmir Metro system serving the Bornova district of İzmir, Turkey.
|
E304446
|
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: Evka-3 station | Statement: [İzmir Metro, hasKeyStation, Evka-3 station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Evka-3 station Context triple: [İzmir Metro, hasKeyStation, Evka-3 station]
-
A.
Gagarina station
Gagarina station is a stop on the Volgograd Metrotram system in Volgograd, Russia, named in honor of cosmonaut Yuri Gagarin.
-
B.
Askim Station
Askim Station is a railway station serving the town of Askim in Viken county, Norway, on the Eastern Østfold Line.
-
C.
Kitasando Station
Kitasando Station is an underground subway station in Shibuya, Tokyo, serving the Tokyo Metro network near the Meiji Shrine and Harajuku area.
-
D.
Pionerskaya station
Pionerskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
E.
Khimvolokno station
Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
- 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: Evka-3 station Triple: [İzmir Metro, hasKeyStation, Evka-3 station]
Generated description
Evka-3 station is a major terminal stop on the İzmir Metro system serving the Bornova district of İzmir, Turkey.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Evka-3 station Target entity description: Evka-3 station is a major terminal stop on the İzmir Metro system serving the Bornova district of İzmir, Turkey.
-
A.
Gagarina station
Gagarina station is a stop on the Volgograd Metrotram system in Volgograd, Russia, named in honor of cosmonaut Yuri Gagarin.
-
B.
Askim Station
Askim Station is a railway station serving the town of Askim in Viken county, Norway, on the Eastern Østfold Line.
-
C.
Kitasando Station
Kitasando Station is an underground subway station in Shibuya, Tokyo, serving the Tokyo Metro network near the Meiji Shrine and Harajuku area.
-
D.
Pionerskaya station
Pionerskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
E.
Khimvolokno station
Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
- 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_69abe08ae5048190a0a3b573d9a5fdbc |
completed | March 7, 2026, 8:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8cbaa4081909ff4e9fdf590e352 |
completed | March 10, 2026, 9:47 a.m. |
| NEDg | Description generation | batch_69afea1732b481909a8df01d80ca1bd4 |
completed | March 10, 2026, 9:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b00eff94b481909a4cc08c8494870c |
completed | March 10, 2026, 12:30 p.m. |
Created at: March 6, 2026, 10:01 p.m.