Triple
T2846274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tram İzmir |
E62990
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Halkapınar |
E303195
|
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: Halkapınar | Statement: [Tram İzmir, hasStation, Halkapınar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halkapınar Context triple: [Tram İzmir, hasStation, Halkapınar]
-
A.
Halkapınar
chosen
Halkapınar is a major transport hub and urban area in İzmir, Turkey, known for its extensive rail and tram connections.
-
B.
Özdamar
Özdamar is the surname of Emine Sevgi Özdamar, a prominent Turkish-German writer, actress, and director known for her works on migration and cultural identity.
-
C.
Alaybey
Alaybey is a neighborhood and tram stop area in the Karşıyaka district of İzmir, Turkey, integrated into the city's modern public transportation network.
-
D.
Birgi
Birgi is a small village in western Sicily, Italy, known for its proximity to Trapani–Birgi Airport and the coastal city of Trapani.
-
E.
Qara Köz
Qara Köz is a mysterious and mesmerizing princess whose beauty and influence drive much of the political and romantic intrigue in Salman Rushdie’s novel *The Enchantress of Florence*.
- 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.