Triple

T5968223
Position Surface form Disambiguated ID Type / Status
Subject Sousse E132805 entity
Predicate nativeName P15 FINISHED
Object سوسة
سوسة هي مدينة ساحلية تونسية تاريخية على البحر الأبيض المتوسط تشتهر بمدينتها العتيقة المصنفة ضمن مواقع التراث العالمي.
 E560936 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: سوسة | Statement: [Sousse, nativeName, سوسة]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: سوسة
Context triple: [Sousse, nativeName, سوسة]
  • A. Tanta
    Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
  • B. Tanta
    Tanta is a small Andean town in Peru known for its high-altitude landscapes and traditional rural life within the Nor Yauyos-Cochas scenic reserve.
  • C. Souk El Trouk
    Souk El Trouk is a traditional market within the historic medina of Tunis, known for its specialized shops and vibrant commercial activity reflecting Ottoman-era influences.
  • D. Mansouriya
    Mansouriya is a residential district in Kuwait City known for its central location within the Al Asimah Governorate.
  • E. Ain Sokhna
    Ain Sokhna is a popular Egyptian Red Sea resort town known for its beaches, proximity to Cairo, and role as a growing industrial and port area.
  • 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: سوسة
Triple: [Sousse, nativeName, سوسة]
Generated description
سوسة هي مدينة ساحلية تونسية تاريخية على البحر الأبيض المتوسط تشتهر بمدينتها العتيقة المصنفة ضمن مواقع التراث العالمي.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: سوسة
Target entity description: سوسة هي مدينة ساحلية تونسية تاريخية على البحر الأبيض المتوسط تشتهر بمدينتها العتيقة المصنفة ضمن مواقع التراث العالمي.
  • A. Tanta
    Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
  • B. Tanta
    Tanta is a small Andean town in Peru known for its high-altitude landscapes and traditional rural life within the Nor Yauyos-Cochas scenic reserve.
  • C. Souk El Trouk
    Souk El Trouk is a traditional market within the historic medina of Tunis, known for its specialized shops and vibrant commercial activity reflecting Ottoman-era influences.
  • D. Mansouriya
    Mansouriya is a residential district in Kuwait City known for its central location within the Al Asimah Governorate.
  • E. Ain Sokhna
    Ain Sokhna is a popular Egyptian Red Sea resort town known for its beaches, proximity to Cairo, and role as a growing industrial and port area.
  • 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_69c0086deab081908550159ca23eec9b completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a3f612481908744cb645f2ede1d completed March 22, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1083b22788190be47b593b30184c6 completed March 23, 2026, 9:30 a.m.
NEDg Description generation batch_69c1095d98c08190b43e84642af701f0 completed March 23, 2026, 9:35 a.m.
NED2 Entity disambiguation (via description) batch_69c10a5e061c81909e8085f3210452dc completed March 23, 2026, 9:39 a.m.
Created at: March 22, 2026, 4:03 p.m.