Triple

T18247392
Position Surface form Disambiguated ID Type / Status
Subject MTA International E436987 entity
Predicate hasPart P35 FINISHED
Object MTA3 Al-Arabia
MTA3 Al-Arabia is an Arabic-language television channel operated by the global Islamic broadcaster MTA International.
 E1313501 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: MTA3 Al-Arabia | Statement: [MTA International, hasPart, MTA3 Al-Arabia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MTA3 Al-Arabia
Context triple: [MTA International, hasPart, MTA3 Al-Arabia]
  • A. Al Mithnab
    Al Mithnab is a town in central Saudi Arabia known as one of the populated localities within the Qassim Region.
  • B. Al Mahara
    Al Mahara is a high-end seafood restaurant in Dubai renowned for its immersive floor-to-ceiling aquarium setting inside the iconic Burj Al Arab hotel.
  • C. Mataf
    Mataf is the open circular area surrounding the Kaaba in Mecca where pilgrims perform the ritual of tawaf by circumambulating the sacred structure.
  • D. Mesaieed
    Mesaieed is an industrial city in Qatar known for its major port facilities and petrochemical industries.
  • E. Al Mashun
    Al Mashun is the namesake of the Great Mosque of Medan, a prominent historic Islamic landmark in Medan, Indonesia.
  • 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: MTA3 Al-Arabia
Triple: [MTA International, hasPart, MTA3 Al-Arabia]
Generated description
MTA3 Al-Arabia is an Arabic-language television channel operated by the global Islamic broadcaster MTA International.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MTA3 Al-Arabia
Target entity description: MTA3 Al-Arabia is an Arabic-language television channel operated by the global Islamic broadcaster MTA International.
  • A. Al Mithnab
    Al Mithnab is a town in central Saudi Arabia known as one of the populated localities within the Qassim Region.
  • B. Al Mahara
    Al Mahara is a high-end seafood restaurant in Dubai renowned for its immersive floor-to-ceiling aquarium setting inside the iconic Burj Al Arab hotel.
  • C. Mataf
    Mataf is the open circular area surrounding the Kaaba in Mecca where pilgrims perform the ritual of tawaf by circumambulating the sacred structure.
  • D. Mesaieed
    Mesaieed is an industrial city in Qatar known for its major port facilities and petrochemical industries.
  • E. Al Mashun
    Al Mashun is the namesake of the Great Mosque of Medan, a prominent historic Islamic landmark in Medan, Indonesia.
  • 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_69d8b91104e08190a8241f7d260a5162 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f7e89b288190a286797ec2cd60a8 completed April 19, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03ac733e708190a7fde1fb61db5d5f completed May 12, 2026, 10:40 p.m.
NEDg Description generation batch_6a03ad2be6e0819081426da968a57db0 completed May 12, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a03ad8898748190b57028bb2e2ed207 completed May 12, 2026, 10:45 p.m.
Created at: April 10, 2026, 10:33 a.m.