Triple

T21590600
Position Surface form Disambiguated ID Type / Status
Subject Imrān E532767 entity
Predicate hasTransliteration P2508 FINISHED
Object Emran
Emran is a transliterated given name derived from the Arabic name Imrān, commonly used in various Muslim-majority cultures.
 E1492060 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: Emran | Statement: [Imrān, hasTransliteration, Emran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Emran
Context triple: [Imrān, hasTransliteration, Emran]
  • A. Faysal
    Faysal is a male given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • B. Miranshah
    Miranshah is the main administrative and commercial town of North Waziristan in Pakistan’s Khyber Pakhtunkhwa province, near the border with Afghanistan.
  • C. Miranshah
    Miranshah was a son of the Turco-Mongol conqueror Timur (Tamerlane) who served as one of his key governors and military commanders in the Timurid Empire.
  • D. Shahriar
    Shahriar is a city in Tehran Province, Iran, known as an urban center within the metropolitan area southwest of Tehran.
  • E. Thadiq
    Thadiq is a town in central Saudi Arabia known for its traditional architecture and location within the Riyadh administrative region.
  • 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: Emran
Triple: [Imrān, hasTransliteration, Emran]
Generated description
Emran is a transliterated given name derived from the Arabic name Imrān, commonly used in various Muslim-majority cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Emran
Target entity description: Emran is a transliterated given name derived from the Arabic name Imrān, commonly used in various Muslim-majority cultures.
  • A. Faysal
    Faysal is a male given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • B. Miranshah
    Miranshah is the main administrative and commercial town of North Waziristan in Pakistan’s Khyber Pakhtunkhwa province, near the border with Afghanistan.
  • C. Miranshah
    Miranshah was a son of the Turco-Mongol conqueror Timur (Tamerlane) who served as one of his key governors and military commanders in the Timurid Empire.
  • D. Shahriar
    Shahriar is a city in Tehran Province, Iran, known as an urban center within the metropolitan area southwest of Tehran.
  • E. Thadiq
    Thadiq is a town in central Saudi Arabia known for its traditional architecture and location within the Riyadh administrative region.
  • 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_69e0c46251648190876f0427cf2d321b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eefadd0ec88190929c76137bd1603e completed April 27, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09f681f8a08190965cf2c3b12eb134 completed May 17, 2026, 5:10 p.m.
NEDg Description generation batch_6a09f85e21948190a6563d309c349f78 completed May 17, 2026, 5:18 p.m.
NED2 Entity disambiguation (via description) batch_6a09f8d30ff08190b3bc6c45f7b5257b completed May 17, 2026, 5:20 p.m.
Created at: April 16, 2026, 6:32 p.m.