Triple

T10987500
Position Surface form Disambiguated ID Type / Status
Subject Mahmoud Mohammed Taha E259667 entity
Predicate familyName P18 FINISHED
Object Taha
Taha is a family name most notably associated with Mahmoud Mohammed Taha, a prominent Sudanese Islamic reformer and thinker.
 E898283 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: Taha | Statement: [Mahmoud Mohammed Taha, familyName, Taha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Taha
Context triple: [Mahmoud Mohammed Taha, familyName, Taha]
  • A. Hasana
    Hasana is a small town in Egypt’s North Sinai Governorate, situated in the Sinai Peninsula.
  • B. Tahir
    Tahir is a common Arabic-origin surname used by various notable individuals across the Muslim world and diaspora.
  • C. Nasr
    Nasr is an ancient Arabian deity, often linked to a vulture or eagle, venerated in parts of pre-Islamic South Arabia.
  • D. Razihi
    Razihi is a highly divergent Arabic-related language spoken by a small community in the mountainous Jabal Razih region of northwestern Yemen.
  • E. Naqa
    Naqa was an ancient city and religious center of the Kingdom of Meroë in what is now Sudan, notable for its well-preserved temples and Kushite-period monuments.
  • 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: Taha
Triple: [Mahmoud Mohammed Taha, familyName, Taha]
Generated description
Taha is a family name most notably associated with Mahmoud Mohammed Taha, a prominent Sudanese Islamic reformer and thinker.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Taha
Target entity description: Taha is a family name most notably associated with Mahmoud Mohammed Taha, a prominent Sudanese Islamic reformer and thinker.
  • A. Hasana
    Hasana is a small town in Egypt’s North Sinai Governorate, situated in the Sinai Peninsula.
  • B. Tahir
    Tahir is a common Arabic-origin surname used by various notable individuals across the Muslim world and diaspora.
  • C. Nasr
    Nasr is an ancient Arabian deity, often linked to a vulture or eagle, venerated in parts of pre-Islamic South Arabia.
  • D. Razihi
    Razihi is a highly divergent Arabic-related language spoken by a small community in the mountainous Jabal Razih region of northwestern Yemen.
  • E. Naqa
    Naqa was an ancient city and religious center of the Kingdom of Meroë in what is now Sudan, notable for its well-preserved temples and Kushite-period monuments.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d787b3c8388190be77e95d56979a7f completed April 9, 2026, 11:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69e344e9c66c81909163cea6aa9276e0 completed April 18, 2026, 8:46 a.m.
NEDg Description generation batch_69e3556e8b408190a02a1fe194ae5750 completed April 18, 2026, 9:57 a.m.
NED2 Entity disambiguation (via description) batch_69e3591ecd548190b049ce95fe3f86d9 completed April 18, 2026, 10:12 a.m.
Created at: April 8, 2026, 9:24 p.m.