Triple

T12739574
Position Surface form Disambiguated ID Type / Status
Subject Karşıyaka E304452 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Nergiz
Nergiz is a neighborhood within the Karşıyaka district of İzmir, Turkey, known as a residential and commercial area on the city’s northern shore.
E1001706 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: Nergiz | Statement: [Karşıyaka, hasNeighbourhood, Nergiz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nergiz
Context triple: [Karşıyaka, hasNeighbourhood, Nergiz]
  • A. Hülya
    Hülya is a feminine given name of Turkish origin commonly used in Turkey and among Turkish communities.
  • B. Nilüfer
    Nilüfer is a modern district and rapidly developing residential and commercial area within the city of Bursa in northwestern Turkey.
  • C. Melek Okyar
    Melek Okyar was the wife of prominent Turkish statesman Fethi Okyar, associated with the early Republican era of Turkey.
  • D. Aysegul Timur
    Aysegul Timur is an academic leader and administrator who serves as president of Florida Gulf Coast University.
  • E. Esra
    Esra is a feminine given name commonly used in Turkey and other countries with Islamic cultural influence.
  • 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: Nergiz
Triple: [Karşıyaka, hasNeighbourhood, Nergiz]
Generated description
Nergiz is a neighborhood within the Karşıyaka district of İzmir, Turkey, known as a residential and commercial area on the city’s northern shore.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nergiz
Target entity description: Nergiz is a neighborhood within the Karşıyaka district of İzmir, Turkey, known as a residential and commercial area on the city’s northern shore.
  • A. Hülya
    Hülya is a feminine given name of Turkish origin commonly used in Turkey and among Turkish communities.
  • B. Nilüfer
    Nilüfer is a modern district and rapidly developing residential and commercial area within the city of Bursa in northwestern Turkey.
  • C. Melek Okyar
    Melek Okyar was the wife of prominent Turkish statesman Fethi Okyar, associated with the early Republican era of Turkey.
  • D. Aysegul Timur
    Aysegul Timur is an academic leader and administrator who serves as president of Florida Gulf Coast University.
  • E. Esra
    Esra is a feminine given name commonly used in Turkey and other countries with Islamic cultural influence.
  • 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_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_69f684eba2508190966d084cc21dc1ea completed May 2, 2026, 11:12 p.m.
NEDg Description generation batch_69f685dac5cc8190b4bc2d81186c9266 completed May 2, 2026, 11:16 p.m.
NED2 Entity disambiguation (via description) batch_69f6869156048190b548ecd04561deb8 completed May 2, 2026, 11:19 p.m.
Created at: April 9, 2026, 5:26 p.m.