Triple

T20649812
Position Surface form Disambiguated ID Type / Status
Subject Anas E507458 entity
Predicate hasVariantSpelling P457 FINISHED
Object Anass
Anass is a masculine given name, commonly used in Arabic-speaking and North African countries, that is a variant spelling of the name Anas.
 E1442366 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: Anass | Statement: [Anas, hasVariantSpelling, Anass]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anass
Context triple: [Anas, hasVariantSpelling, Anass]
  • A. Nizar
    Nizar is a masculine given name most famously associated with the Syrian poet and diplomat Nizar Qabbani.
  • B. Nichan el-Anouar
    Nichan el-Anouar is the namesake of the Ordre du Nichan El-Anouar, a historical honorific order associated with French colonial-era decorations.
  • C. Sahnun
    Sahnun was a prominent 9th-century Islamic jurist from North Africa whose compilation of legal opinions, the Mudawwana, became a foundational text of the Maliki school of Sunni jurisprudence.
  • D. Belhamed
    Belhamed is a locality in Libya that was the site of significant fighting during World War II’s North African campaign.
  • E. Mounir
    Mounir is a masculine given name of Arabic origin, commonly used in various Arabic-speaking and Muslim-majority countries.
  • 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: Anass
Triple: [Anas, hasVariantSpelling, Anass]
Generated description
Anass is a masculine given name, commonly used in Arabic-speaking and North African countries, that is a variant spelling of the name Anas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anass
Target entity description: Anass is a masculine given name, commonly used in Arabic-speaking and North African countries, that is a variant spelling of the name Anas.
  • A. Nizar
    Nizar is a masculine given name most famously associated with the Syrian poet and diplomat Nizar Qabbani.
  • B. Nichan el-Anouar
    Nichan el-Anouar is the namesake of the Ordre du Nichan El-Anouar, a historical honorific order associated with French colonial-era decorations.
  • C. Sahnun
    Sahnun was a prominent 9th-century Islamic jurist from North Africa whose compilation of legal opinions, the Mudawwana, became a foundational text of the Maliki school of Sunni jurisprudence.
  • D. Belhamed
    Belhamed is a locality in Libya that was the site of significant fighting during World War II’s North African campaign.
  • E. Mounir
    Mounir is a masculine given name of Arabic origin, commonly used in various Arabic-speaking and Muslim-majority countries.
  • 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_69e0b4bf58c081908e52a4500e03ff83 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6af2133048190a6308074a3b3347e completed April 20, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08c59354388190b5c2a0c1bdd14575 completed May 16, 2026, 7:29 p.m.
NEDg Description generation batch_6a08c648e35881908c480b0afa383422 completed May 16, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_6a08c6c6f9608190bdbcdd58f6b14008 completed May 16, 2026, 7:34 p.m.
Created at: April 16, 2026, 11:43 a.m.