Triple

T2837437
Position Surface form Disambiguated ID Type / Status
Subject İzmir Metro E62383 entity
Predicate connectsDistrict P2564 FINISHED
Object Karabağlar
Karabağlar is a populous urban district of İzmir, Turkey, known primarily as a residential and commercial area within the city’s metropolitan region.
 E304449 NE FINISHED

How this triple was built (4 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: Karabağlar | Statement: [İzmir Metro, connectsDistrict, Karabağlar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Karabağlar
Context triple: [İzmir Metro, connectsDistrict, Karabağlar]
  • A. Beştepe
    Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
  • B. Cabadbaran
    Cabadbaran is a component city in the Caraga region of the Philippines, serving as the capital of the province of Agusan del Norte.
  • C. Kaymaklı
    Kaymaklı is an ancient multi-level underground city in Turkey’s Cappadocia region, renowned for its extensive tunnels, living quarters, and historical use as a refuge.
  • D. 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*.
  • E. Karaköy
    Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Karabağlar
Triple: [İzmir Metro, connectsDistrict, Karabağlar]
Generated description
Karabağlar is a populous urban district of İzmir, Turkey, known primarily as a residential and commercial area within the city’s metropolitan region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Karabağlar
Target entity description: Karabağlar is a populous urban district of İzmir, Turkey, known primarily as a residential and commercial area within the city’s metropolitan region.
  • A. Beştepe
    Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
  • B. Cabadbaran
    Cabadbaran is a component city in the Caraga region of the Philippines, serving as the capital of the province of Agusan del Norte.
  • C. Kaymaklı
    Kaymaklı is an ancient multi-level underground city in Turkey’s Cappadocia region, renowned for its extensive tunnels, living quarters, and historical use as a refuge.
  • D. 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*.
  • E. Karaköy
    Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
  • F. None of above. chosen

Provenance (5 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_69ab4c3c39188190955b9c49d98463d8 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdeede0488190a9782f55b57559ee completed March 7, 2026, 8:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8cbaa4081909ff4e9fdf590e352 completed March 10, 2026, 9:47 a.m.
NEDg Description generation batch_69afea1732b481909a8df01d80ca1bd4 completed March 10, 2026, 9:53 a.m.
NED2 Entity disambiguation (via description) batch_69b00eff94b481909a4cc08c8494870c completed March 10, 2026, 12:30 p.m.
Created at: March 6, 2026, 10:01 p.m.