Triple

T3351007
Position Surface form Disambiguated ID Type / Status
Subject Dilan Yeşilgöz-Zegerius E70491 entity
Predicate givenName P17 FINISHED
Object Dilan
Dilan is a given name shared by various individuals, including Dutch politician Dilan Yeşilgöz-Zegerius.
 E351544 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: Dilan | Statement: [Dilan Yeşilgöz-Zegerius, givenName, Dilan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dilan
Context triple: [Dilan Yeşilgöz-Zegerius, givenName, Dilan]
  • A. Tareeno
    Tareeno is an alternative name for Wanetsi, an Eastern Iranian language closely related to Pashto and spoken primarily in parts of Pakistan and Afghanistan.
  • B. Lehna
    Lehna, later known as Guru Angad, was the second Sikh Guru and a key early leader in consolidating and spreading Sikhism after Guru Nanak.
  • C. Devdas
    Devdas is a classic Bengali novel by Sarat Chandra Chattopadhyay that tells the tragic love story of a wealthy young man unable to unite with his childhood sweetheart, making it one of the most iconic works in Indian literature and cinema.
  • D. Sadyattes
    Sadyattes was an early king of ancient Lydia, known primarily as the father of Alyattes and a predecessor in the Mermnad dynasty that ruled western Anatolia.
  • E. Badal
    Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
  • 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: Dilan
Triple: [Dilan Yeşilgöz-Zegerius, givenName, Dilan]
Generated description
Dilan is a given name shared by various individuals, including Dutch politician Dilan Yeşilgöz-Zegerius.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dilan
Target entity description: Dilan is a given name shared by various individuals, including Dutch politician Dilan Yeşilgöz-Zegerius.
  • A. Tareeno
    Tareeno is an alternative name for Wanetsi, an Eastern Iranian language closely related to Pashto and spoken primarily in parts of Pakistan and Afghanistan.
  • B. Lehna
    Lehna, later known as Guru Angad, was the second Sikh Guru and a key early leader in consolidating and spreading Sikhism after Guru Nanak.
  • C. Devdas
    Devdas is a classic Bengali novel by Sarat Chandra Chattopadhyay that tells the tragic love story of a wealthy young man unable to unite with his childhood sweetheart, making it one of the most iconic works in Indian literature and cinema.
  • D. Sadyattes
    Sadyattes was an early king of ancient Lydia, known primarily as the father of Alyattes and a predecessor in the Mermnad dynasty that ruled western Anatolia.
  • E. Badal
    Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
  • 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_69ad85a4ef7c8190a29e2bbd6fa454e4 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb220721c81909eb4d8d35c923927 completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3252f3f248190bb61db5c4fd2781a completed March 12, 2026, 8:42 p.m.
NEDg Description generation batch_69b3290aa6dc8190bd45ec83094fc23e completed March 12, 2026, 8:58 p.m.
NED2 Entity disambiguation (via description) batch_69b32987fdb48190983babe4515c68b4 completed March 12, 2026, 9 p.m.
Created at: March 8, 2026, 3:12 p.m.