Triple

T16562119
Position Surface form Disambiguated ID Type / Status
Subject Saied E402363 entity
Predicate transliterationOf P5923 FINISHED
Object سعيد
سعيد هو اسم علم عربي شائع يُستخدم للذكور ويعني "السعيد" أو "المحظوظ".
 E1219164 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: سعيد | Statement: [Saied, transliterationOf, سعيد]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: سعيد
Context triple: [Saied, transliterationOf, سعيد]
  • A. سوسة
    سوسة هي مدينة ساحلية تونسية تاريخية على البحر الأبيض المتوسط تشتهر بمدينتها العتيقة المصنفة ضمن مواقع التراث العالمي.
  • B. Saada
    Saada is a city and governorate in northern Yemen known as a stronghold and historical center of the Houthi movement.
  • C. Sufriyya
    Sufriyya is a historical Islamic sect that emerged as a moderate branch of the Kharijites, known for its distinct theological and political positions in early Islamic history.
  • D. Siraf
    Siraf was a major medieval Persian Gulf port city and trading hub that played a key role in Islamic maritime commerce between the Middle East, India, and East Africa.
  • E. Sanaa
    Sanaa is a table-service restaurant at Disney’s Animal Kingdom Lodge known for its African-inspired cuisine with Indian flavors and savanna views of roaming wildlife.
  • 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: سعيد
Triple: [Saied, transliterationOf, سعيد]
Generated description
سعيد هو اسم علم عربي شائع يُستخدم للذكور ويعني "السعيد" أو "المحظوظ".
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: سعيد
Target entity description: سعيد هو اسم علم عربي شائع يُستخدم للذكور ويعني "السعيد" أو "المحظوظ".
  • A. سوسة
    سوسة هي مدينة ساحلية تونسية تاريخية على البحر الأبيض المتوسط تشتهر بمدينتها العتيقة المصنفة ضمن مواقع التراث العالمي.
  • B. Saada
    Saada is a city and governorate in northern Yemen known as a stronghold and historical center of the Houthi movement.
  • C. Sufriyya
    Sufriyya is a historical Islamic sect that emerged as a moderate branch of the Kharijites, known for its distinct theological and political positions in early Islamic history.
  • D. Siraf
    Siraf was a major medieval Persian Gulf port city and trading hub that played a key role in Islamic maritime commerce between the Middle East, India, and East Africa.
  • E. Sanaa
    Sanaa is a table-service restaurant at Disney’s Animal Kingdom Lodge known for its African-inspired cuisine with Indian flavors and savanna views of roaming wildlife.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3576eb63081908cb5dc6c0a8a13ac completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067bfcf78819082bf1a15eebdab86 completed May 10, 2026, 11:10 a.m.
NEDg Description generation batch_6a0068172dbc8190850051968e3cd133 completed May 10, 2026, 11:12 a.m.
NED2 Entity disambiguation (via description) batch_6a006872e5f48190aa76611fcbd0c455 completed May 10, 2026, 11:13 a.m.
Created at: April 10, 2026, 5:15 a.m.