Triple

T10337292
Position Surface form Disambiguated ID Type / Status
Subject الكتاب E243039 entity
Predicate شرح P87652 FINISHED
Object الرماني
الرماني هو عالم لغوي ومفسر نحوي عربي بارز من علماء القرن الرابع الهجري، عُرف بشرحه للكتب اللغوية والبلاغية وتفسير القرآن.
 E856818 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: الرماني | Statement: [الكتاب, شرح, الرماني]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: الرماني
Context triple: [الكتاب, شرح, الرماني]
  • A. Rutba
    Rutba is a remote desert town in western Iraq that serves as a key transit point on the highway linking Baghdad with Jordan and Syria.
  • B. Razihi
    Razihi is a highly divergent Arabic-related language spoken by a small community in the mountainous Jabal Razih region of northwestern Yemen.
  • C. Rommen
    Rommen is a neighborhood in Oslo, Norway, situated within the Søndre Nordstrand borough.
  • D. Arbela
    Arbela is the ancient name of the modern city of Erbil in Iraqi Kurdistan, historically known as a major Assyrian and later Hellenistic center near the site of Alexander the Great’s victory at the Battle of Gaugamela.
  • E. Raban
    Raban is the surname of Jonathan Raban, a British travel writer and novelist known for his reflective and genre-blending works.
  • 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: الرماني
Triple: [الكتاب, شرح, الرماني]
Generated description
الرماني هو عالم لغوي ومفسر نحوي عربي بارز من علماء القرن الرابع الهجري، عُرف بشرحه للكتب اللغوية والبلاغية وتفسير القرآن.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: الرماني
Target entity description: الرماني هو عالم لغوي ومفسر نحوي عربي بارز من علماء القرن الرابع الهجري، عُرف بشرحه للكتب اللغوية والبلاغية وتفسير القرآن.
  • A. Rutba
    Rutba is a remote desert town in western Iraq that serves as a key transit point on the highway linking Baghdad with Jordan and Syria.
  • B. Razihi
    Razihi is a highly divergent Arabic-related language spoken by a small community in the mountainous Jabal Razih region of northwestern Yemen.
  • C. Rommen
    Rommen is a neighborhood in Oslo, Norway, situated within the Søndre Nordstrand borough.
  • D. Arbela
    Arbela is the ancient name of the modern city of Erbil in Iraqi Kurdistan, historically known as a major Assyrian and later Hellenistic center near the site of Alexander the Great’s victory at the Battle of Gaugamela.
  • E. Raban
    Raban is the surname of Jonathan Raban, a British travel writer and novelist known for his reflective and genre-blending works.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fb99ef088190b64661b2f42c320e completed April 7, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d7506278f881908b090b13706e5d4e completed April 9, 2026, 7:08 a.m.
NEDg Description generation batch_69d75133588c819093af59327b951cd7 completed April 9, 2026, 7:11 a.m.
NED2 Entity disambiguation (via description) batch_69d751d4aa908190a825322ebf0066af completed April 9, 2026, 7:14 a.m.
Created at: April 6, 2026, 11:54 a.m.