Triple
T12739255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | İzmir urban transport network |
E304444
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Torbalı |
E317911
|
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: Torbalı | Statement: [İzmir urban transport network, connects, Torbalı]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torbalı Context triple: [İzmir urban transport network, connects, Torbalı]
-
A.
Torbalı
chosen
Torbalı is a district and rapidly growing suburban area of İzmir, Turkey, known for its industrial zones and connection to the city via the İZBAN commuter rail system.
-
B.
Ayvacık
Ayvacık is a small town and district in Turkey’s Çanakkale Province, known for its traditional stone houses and proximity to the Aegean coast and ancient sites like Assos.
-
C.
Ayvacık
Ayvacık is a rural district and town in Turkey’s Black Sea region, located within Samsun Province and known for its natural landscapes and agricultural character.
-
D.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
E.
Güzelyurt
Güzelyurt is a historic town in Turkey’s Cappadocia region, known for its rock-cut churches, underground cities, and scenic valleys.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9646dfc908190bc398935d1d23537 |
completed | April 10, 2026, 8:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0d12cd88190b6e205ad98296ed9 |
completed | May 3, 2026, 9:40 p.m. |
Created at: April 9, 2026, 5:26 p.m.