Triple
T2846255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tram İzmir |
E62990
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object | Konak Tram |
E62990
|
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: Konak Tram | Statement: [Tram İzmir, hasLine, Konak Tram]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Konak Tram Context triple: [Tram İzmir, hasLine, Konak Tram]
-
A.
Tram Izmir
chosen
Tram Izmir is a modern light rail tram network serving the Turkish city of İzmir as part of its urban public transportation system.
-
B.
Istanbul Metro
The Istanbul Metro is a rapid transit system serving Istanbul, Turkey, connecting key districts and transport hubs across the city.
-
C.
Santa Teresa Tram
The Santa Teresa Tram is a historic yellow streetcar line in Rio de Janeiro that carries passengers through the hilly, bohemian Santa Teresa neighborhood and across the iconic Arcos da Lapa aqueduct.
-
D.
Tram 18
Tram 18 is a tram line in Geneva’s public transport system that connects key districts within the city and its surrounding areas.
-
E.
Ankara Metro
Ankara Metro is the rapid transit system serving Turkey's capital city, providing urban rail transportation across Ankara and its surrounding districts.
- 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_69ab4c407c408190857d25e027155ce9 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf3d00708190966a477fdd855f23 |
completed | March 7, 2026, 8:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01d7c84e8819098089bd1c6874189 |
completed | March 10, 2026, 1:32 p.m. |
Created at: March 6, 2026, 10:02 p.m.