Triple

T10480039
Position Surface form Disambiguated ID Type / Status
Subject Al-Farrāʾ E247145 entity
Predicate notableWork P4 FINISHED
Object al-Nawādir
al-Nawādir is a classical Arabic linguistic work by the grammarian Al-Farrāʾ, known for its collection of rare expressions and grammatical observations.
 E865943 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: al-Nawādir | Statement: [Al-Farrāʾ, notableWork, al-Nawādir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: al-Nawādir
Context triple: [Al-Farrāʾ, notableWork, al-Nawādir]
  • A. An-Najm
    An-Najm is the 53rd chapter of the Qur’an, known for its powerful verses affirming the Prophet Muhammad’s divine revelation and warning against idolatry.
  • B. al-Natsha
    al-Natsha is an alternative transliteration of the Arabic surname al-Natsheh, commonly borne by Palestinian families.
  • C. al-Nabigha
    al-Nabigha was an Arab woman of pre-Islamic Mecca best known as the mother of the prominent early Islamic military commander and statesman Amr ibn al-As.
  • D. Nawaf
    Nawaf is a masculine given name commonly used in Arabic-speaking countries, often associated with nobility and leadership.
  • E. Nasr
    Nasr is an ancient Arabian deity, often linked to a vulture or eagle, venerated in parts of pre-Islamic South Arabia.
  • 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: al-Nawādir
Triple: [Al-Farrāʾ, notableWork, al-Nawādir]
Generated description
al-Nawādir is a classical Arabic linguistic work by the grammarian Al-Farrāʾ, known for its collection of rare expressions and grammatical observations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: al-Nawādir
Target entity description: al-Nawādir is a classical Arabic linguistic work by the grammarian Al-Farrāʾ, known for its collection of rare expressions and grammatical observations.
  • A. An-Najm
    An-Najm is the 53rd chapter of the Qur’an, known for its powerful verses affirming the Prophet Muhammad’s divine revelation and warning against idolatry.
  • B. al-Natsha
    al-Natsha is an alternative transliteration of the Arabic surname al-Natsheh, commonly borne by Palestinian families.
  • C. al-Nabigha
    al-Nabigha was an Arab woman of pre-Islamic Mecca best known as the mother of the prominent early Islamic military commander and statesman Amr ibn al-As.
  • D. Nawaf
    Nawaf is a masculine given name commonly used in Arabic-speaking countries, often associated with nobility and leadership.
  • E. Nasr
    Nasr is an ancient Arabian deity, often linked to a vulture or eagle, venerated in parts of pre-Islamic South Arabia.
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5095b2ec881909e1220d83e750a75 completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8a02aa2748190902f5c08afd7dda9 completed April 10, 2026, 7 a.m.
NEDg Description generation batch_69d8a2f4bbec8190a5c508c6431d71b2 completed April 10, 2026, 7:12 a.m.
NED2 Entity disambiguation (via description) batch_69d8aff34c7081909c3504e00f56d9ec completed April 10, 2026, 8:08 a.m.
Created at: April 6, 2026, 12:22 p.m.