Triple

T8597816
Position Surface form Disambiguated ID Type / Status
Subject Beykoz E203594 entity
Predicate contains P35 FINISHED
Object Kanlıca
Kanlıca is a historic Bosphorus neighborhood on Istanbul’s Asian side, famed for its waterfront views and traditional thick yogurt.
 E772249 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: Kanlıca | Statement: [Beykoz, contains, Kanlıca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kanlıca
Context triple: [Beykoz, contains, Kanlıca]
  • A. Zeytinburnu
    Zeytinburnu is a densely populated working- and middle-class district on Istanbul’s European side, known as an early industrial area and a key transport hub within the city.
  • B. Marmaraereğlisi
    Marmaraereğlisi is a coastal town and district on the northern shore of the Sea of Marmara in northwestern Turkey, known for its beaches and proximity to Istanbul.
  • C. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • D. Maltepe
    Maltepe is a residential and commercial district on Istanbul’s Asian side along the Sea of Marmara.
  • E. Kanık
    Kanık is the surname of the influential Turkish poet Orhan Veli Kanık, a leading figure in modern Turkish literature and the Garip movement.
  • 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: Kanlıca
Triple: [Beykoz, contains, Kanlıca]
Generated description
Kanlıca is a historic Bosphorus neighborhood on Istanbul’s Asian side, famed for its waterfront views and traditional thick yogurt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kanlıca
Target entity description: Kanlıca is a historic Bosphorus neighborhood on Istanbul’s Asian side, famed for its waterfront views and traditional thick yogurt.
  • A. Zeytinburnu
    Zeytinburnu is a densely populated working- and middle-class district on Istanbul’s European side, known as an early industrial area and a key transport hub within the city.
  • B. Marmaraereğlisi
    Marmaraereğlisi is a coastal town and district on the northern shore of the Sea of Marmara in northwestern Turkey, known for its beaches and proximity to Istanbul.
  • C. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • D. Maltepe
    Maltepe is a residential and commercial district on Istanbul’s Asian side along the Sea of Marmara.
  • E. Kanık
    Kanık is the surname of the influential Turkish poet Orhan Veli Kanık, a leading figure in modern Turkish literature and the Garip movement.
  • 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46cacbe88190b95beeedc9f480b0 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb759f6c819085939e38e0281361 completed April 3, 2026, 3:23 p.m.
NEDg Description generation batch_69cfdbeba3808190b3d11a45bce24c80 completed April 3, 2026, 3:25 p.m.
NED2 Entity disambiguation (via description) batch_69cfdc391e6081909b1f3ff823ce174d completed April 3, 2026, 3:26 p.m.
Created at: March 30, 2026, 6:24 p.m.