Triple

T14714518
Position Surface form Disambiguated ID Type / Status
Subject Diyâr-ı Bekr E345641 entity
Predicate hasAlternativeName P39 FINISHED
Object Diyâr Bekr
Diyâr Bekr is a historical name used in the medieval Islamic world for the region around the city of Diyarbakır in southeastern Anatolia.
 E1118401 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: Diyâr Bekr | Statement: [Diyâr-ı Bekr, hasAlternativeName, Diyâr Bekr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Diyâr Bekr
Context triple: [Diyâr-ı Bekr, hasAlternativeName, Diyâr Bekr]
  • A. Kadir
    Kadir is a masculine given name of Turkish origin commonly used in Turkey and among Turkish-speaking communities.
  • B. 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.
  • C. Belqasim
    Belqasim is a personal given name of Arabic origin, used primarily in North African and Middle Eastern cultures.
  • D. Bawshar
    Bawshar is a district in Muscat, Oman, known as a major urban area that includes important landmarks, commercial centers, and residential neighborhoods.
  • E. Djoum
    Djoum is a small town in southern Cameroon known as a local administrative and trading center within the country's South 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: Diyâr Bekr
Triple: [Diyâr-ı Bekr, hasAlternativeName, Diyâr Bekr]
Generated description
Diyâr Bekr is a historical name used in the medieval Islamic world for the region around the city of Diyarbakır in southeastern Anatolia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Diyâr Bekr
Target entity description: Diyâr Bekr is a historical name used in the medieval Islamic world for the region around the city of Diyarbakır in southeastern Anatolia.
  • A. Kadir
    Kadir is a masculine given name of Turkish origin commonly used in Turkey and among Turkish-speaking communities.
  • B. 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.
  • C. Belqasim
    Belqasim is a personal given name of Arabic origin, used primarily in North African and Middle Eastern cultures.
  • D. Bawshar
    Bawshar is a district in Muscat, Oman, known as a major urban area that includes important landmarks, commercial centers, and residential neighborhoods.
  • E. Djoum
    Djoum is a small town in southern Cameroon known as a local administrative and trading center within the country's South 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb98513b081908b230f6ac79c72ad completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0ce17f688190a86979cca8b88494 completed May 8, 2026, 4:18 p.m.
NEDg Description generation batch_69fe1547d7f8819097b2bdf3b8a10751 completed May 8, 2026, 4:54 p.m.
NED2 Entity disambiguation (via description) batch_69fe15ddc6ac819098c981367b970077 completed May 8, 2026, 4:57 p.m.
Created at: April 10, 2026, 1:29 a.m.