Triple

T5918722
Position Surface form Disambiguated ID Type / Status
Subject Youssef Chahine E131647 entity
Predicate notableWork P4 FINISHED
Object Al-Mohager
Al-Mohager is a 1994 Egyptian historical drama film by director Youssef Chahine that offers a modern, allegorical retelling of the biblical story of Joseph.
E556960 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-Mohager | Statement: [Youssef Chahine, notableWork, Al-Mohager]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Al-Mohager
Context triple: [Youssef Chahine, notableWork, Al-Mohager]
  • A. Al-Hareeq
    Al-Hareeq is a town in central Saudi Arabia known for its agricultural activity, particularly date palm cultivation, within the Riyadh region.
  • B. Hammad
    Hammad is a character in the novel "Falling Man," which explores the aftermath of the September 11 attacks.
  • C. Abu al-Ula
    Abu al-Ula was a Muslim ruler in medieval Seville under whose authority the iconic Torre del Oro was constructed.
  • D. Umara
    Umara is the plural form of the Arabic name or title "Amir," commonly used to refer to multiple rulers or princes.
  • E. As-Samad
    As-Samad is one of the names of Allah in Islam, signifying the One who is absolutely self-sufficient, eternally depended upon by all creation, and free of all need.
  • 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-Mohager
Triple: [Youssef Chahine, notableWork, Al-Mohager]
Generated description
Al-Mohager is a 1994 Egyptian historical drama film by director Youssef Chahine that offers a modern, allegorical retelling of the biblical story of Joseph.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Al-Mohager
Target entity description: Al-Mohager is a 1994 Egyptian historical drama film by director Youssef Chahine that offers a modern, allegorical retelling of the biblical story of Joseph.
  • A. Al-Hareeq
    Al-Hareeq is a town in central Saudi Arabia known for its agricultural activity, particularly date palm cultivation, within the Riyadh region.
  • B. Hammad
    Hammad is a character in the novel "Falling Man," which explores the aftermath of the September 11 attacks.
  • C. Abu al-Ula
    Abu al-Ula was a Muslim ruler in medieval Seville under whose authority the iconic Torre del Oro was constructed.
  • D. Umara
    Umara is the plural form of the Arabic name or title "Amir," commonly used to refer to multiple rulers or princes.
  • E. As-Samad
    As-Samad is one of the names of Allah in Islam, signifying the One who is absolutely self-sufficient, eternally depended upon by all creation, and free of all need.
  • 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_69c0085a1ed08190a7e9a8b6323fd680 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c038003c408190b2a89df0b759dcbf completed March 22, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c033d59481909495192af85307b7 completed March 23, 2026, 4:23 a.m.
NEDg Description generation batch_69c0c1bf78908190933360b1099b1444 completed March 23, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_69c0c240c3ac8190895c621c3d326bfd completed March 23, 2026, 4:32 a.m.
Created at: March 22, 2026, 4 p.m.