Triple

T12739254
Position Surface form Disambiguated ID Type / Status
Subject İzmir urban transport network E304444 entity
Predicate connects P390 FINISHED
Object Aliağa E309020 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: Aliağa | Statement: [İzmir urban transport network, connects, Aliağa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aliağa
Context triple: [İzmir urban transport network, connects, Aliağa]
  • A. Aliağa chosen
    Aliağa is a coastal industrial district and port town in İzmir Province, Turkey, known for its petrochemical facilities and ship-breaking yards.
  • B. Yalıköy
    Yalıköy is a neighborhood in the Beykoz district of Istanbul, Turkey, known for its residential character and proximity to the Bosphorus.
  • C. Torbalı
    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.
  • D. Kemalpaşa
    Kemalpaşa is a district and town in western Turkey known for its cherry production and proximity to the city of İzmir.
  • E. Kırcaali
    Kırcaali (Kardzhali) is a city in southern Bulgaria known as a regional center in the Eastern Rhodope Mountains with a significant historical Turkish population.
  • 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_69f7b8be7834819085bfce037c467004 completed May 3, 2026, 9:06 p.m.
Created at: April 9, 2026, 5:26 p.m.