Triple

T7281640
Position Surface form Disambiguated ID Type / Status
Subject Yıldız Kenter E163162 entity
Predicate familyName P18 FINISHED
Object Kenter
Kenter is a Turkish surname most prominently associated with the acclaimed stage and film actress Yıldız Kenter and her family of influential theatre artists.
 E654094 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: Kenter | Statement: [Yıldız Kenter, familyName, Kenter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kenter
Context triple: [Yıldız Kenter, familyName, Kenter]
  • A. Gouderak
    Gouderak is a small village in the Dutch province of South Holland, situated along the Hollandse IJssel river.
  • B. Gharaunda
    Gharaunda is a town in the Indian state of Haryana known for its agricultural market and proximity to the historic city of Karnal.
  • C. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • D. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • E. Kwintsheul
    Kwintsheul is a village in the Dutch province of South Holland, known for its greenhouse horticulture and location within the Westland region.
  • 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: Kenter
Triple: [Yıldız Kenter, familyName, Kenter]
Generated description
Kenter is a Turkish surname most prominently associated with the acclaimed stage and film actress Yıldız Kenter and her family of influential theatre artists.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kenter
Target entity description: Kenter is a Turkish surname most prominently associated with the acclaimed stage and film actress Yıldız Kenter and her family of influential theatre artists.
  • A. Gouderak
    Gouderak is a small village in the Dutch province of South Holland, situated along the Hollandse IJssel river.
  • B. Gharaunda
    Gharaunda is a town in the Indian state of Haryana known for its agricultural market and proximity to the historic city of Karnal.
  • C. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • D. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • E. Kwintsheul
    Kwintsheul is a village in the Dutch province of South Holland, known for its greenhouse horticulture and location within the Westland region.
  • 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_69c6885c5964819085b209701769877f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb34fe0c8190a642fd3339f0cacd completed March 27, 2026, 8:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db379e1c81908ebd4c44504ce5fb completed March 28, 2026, 1:44 p.m.
NEDg Description generation batch_69c7df4788e081908ccc162125c6550d completed March 28, 2026, 2:01 p.m.
NED2 Entity disambiguation (via description) batch_69c7dfa826d081909129df80cca13daa completed March 28, 2026, 2:03 p.m.
Created at: March 27, 2026, 2:59 p.m.