Triple

T36512939
Position Surface form Disambiguated ID Type / Status
Subject Ilham Aliyev E899958 entity
Predicate child P120 FINISHED
Object Arzu Aliyeva
Arzu Aliyeva is an Azerbaijani film producer and public figure, best known as the daughter of Azerbaijan’s president Ilham Aliyev.
E2193860 NE FINISHED

How this triple was built (2 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: Arzu Aliyeva | Statement: [Ilham Aliyev, child, Arzu Aliyeva]
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: Arzu Aliyeva
Triple: [Ilham Aliyev, child, Arzu Aliyeva]
Generated description
Arzu Aliyeva is an Azerbaijani film producer and public figure, best known as the daughter of Azerbaijan’s president Ilham Aliyev.

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_69f76e5dada881909da2d34bc7a9202a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c1f0c3b4819098be0aedf3747138 completed May 3, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a20b517bc81909465e6f5c0d9bf5b completed June 23, 2026, 5:59 a.m.
NEDg Description generation batch_6a3a24f388948190be0d737c9f6e4b36 completed June 23, 2026, 6:17 a.m.
NED2 Entity disambiguation (via description) batch_6a3a256da03c8190bd78911129930e13 completed June 23, 2026, 6:19 a.m.
Created at: May 3, 2026, 4:10 p.m.