Triple

T16102193
Position Surface form Disambiguated ID Type / Status
Subject Nazli Sabri E390647 entity
Predicate givenName P17 FINISHED
Object Nazli
Nazli is a feminine given name of Persian and Turkish origin, commonly used in various Middle Eastern and Balkan cultures.
E1194245 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: Nazli | Statement: [Nazli Sabri, givenName, Nazli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nazli
Context triple: [Nazli Sabri, givenName, Nazli]
  • A. Zinya
    Zinya is a diminutive, affectionate form of the Russian male given name Zinovy.
  • B. Nazli Hanem
    Nazli Hanem was an Egyptian princess and Ottoman noblewoman, best known as a daughter of the powerful 19th-century ruler Muhammad Ali Pasha.
  • C. Zohra
    Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
  • D. Farzana
    Farzana is an individual known primarily as the spouse of Hassan.
  • E. Anizah
    Anizah is a prominent Arab tribal confederation historically associated with the Najd region of the Arabian Peninsula.
  • 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: Nazli
Triple: [Nazli Sabri, givenName, Nazli]
Generated description
Nazli is a feminine given name of Persian and Turkish origin, commonly used in various Middle Eastern and Balkan cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nazli
Target entity description: Nazli is a feminine given name of Persian and Turkish origin, commonly used in various Middle Eastern and Balkan cultures.
  • A. Zinya
    Zinya is a diminutive, affectionate form of the Russian male given name Zinovy.
  • B. Nazli Hanem
    Nazli Hanem was an Egyptian princess and Ottoman noblewoman, best known as a daughter of the powerful 19th-century ruler Muhammad Ali Pasha.
  • C. Zohra
    Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
  • D. Farzana
    Farzana is an individual known primarily as the spouse of Hassan.
  • E. Anizah
    Anizah is a prominent Arab tribal confederation historically associated with the Najd region of the Arabian Peninsula.
  • 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_69d87f1a8dd881909f1de6ef78849874 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6976ec8190b499e99b196b0285 completed April 17, 2026, 9:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeba007c08190bf4d3cf092abc7dd completed May 10, 2026, 2:21 a.m.
NEDg Description generation batch_69ffecb8c71481908b4913bb078b6415 completed May 10, 2026, 2:26 a.m.
NED2 Entity disambiguation (via description) batch_69ffed469a5c8190932fa4ebc44358c4 completed May 10, 2026, 2:28 a.m.
Created at: April 10, 2026, 5 a.m.