Triple

T12715648
Position Surface form Disambiguated ID Type / Status
Subject Asma al-Assad E303831 entity
Predicate givenName P17 FINISHED
Object Asma E757412 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: Asma | Statement: [Asma al-Assad, givenName, Asma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asma
Context triple: [Asma al-Assad, givenName, Asma]
  • A. Asmaa chosen
    Asmaa is a feminine given name of Arabic origin commonly used in many Muslim-majority countries.
  • B. Amna
    Amna is a central female character in the Egyptian film "The Nightingale's Prayer," whose tragic story explores themes of honor, revenge, and social oppression.
  • C. Zahra
    Zahra is the given name of Princess Zahra Aga Khan, a prominent member of the Aga Khan family known for her work in international development and philanthropy.
  • D. Asma ul Husna
    Asma ul Husna refers to the 99 beautiful names of Allah in Islamic tradition, each expressing a distinct divine attribute.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9620bd6148190a2f50067a4c18c14 completed April 10, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671bad5108190915d14c3ec3d2e27 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:23 p.m.