Triple

T12739252
Position Surface form Disambiguated ID Type / Status
Subject İzmir urban transport network E304444 entity
Predicate connects P390 FINISHED
Object Gaziemir E285088 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: Gaziemir | Statement: [İzmir urban transport network, connects, Gaziemir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaziemir
Context triple: [İzmir urban transport network, connects, Gaziemir]
  • A. Gaziemir chosen
    Gaziemir is a district of İzmir, Turkey, known for its proximity to the city’s main international airport and its role as a growing residential and commercial hub.
  • B. Kasimov
    Kasimov is a historic town in central Russia known for its Tatar heritage, medieval architecture, and location on the Oka River.
  • C. Gudermes
    Gudermes is a town in the Chechen Republic of Russia that serves as an important regional transport and administrative center.
  • D. Yamburg
    Yamburg is the former name of the Russian town now known as Kingisepp, located in Leningrad Oblast near the border with Estonia.
  • E. Demerdzhi
    Demerdzhi is a notable mountain massif in Crimea, famous for its striking rock formations and scenic landscapes.
  • 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_69d9646cfcac81909283dca987755c0e completed April 10, 2026, 8:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684eba2508190966d084cc21dc1ea completed May 2, 2026, 11:12 p.m.
Created at: April 9, 2026, 5:26 p.m.