Triple

T15741636
Position Surface form Disambiguated ID Type / Status
Subject Arabic Lām E381615 entity
Predicate nameInArabic P6450 FINISHED
Object لام
لام هو الحرف الثالث والعشرون في الأبجدية العربية ويُستخدم لتمثيل صوت /l/ في اللغة العربية والعديد من اللغات الأخرى المكتوبة بالحرف العربي.
 E1173839 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: لام | Statement: [Arabic Lām, nameInArabic, لام]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: لام
Context triple: [Arabic Lām, nameInArabic, لام]
  • A. Lagus
    Lagus was a Macedonian nobleman traditionally regarded as the father of Ptolemy I Soter, the founder of Egypt’s Ptolemaic dynasty.
  • B. La
    La is a coastal town in the Greater Accra Region of Ghana, known as one of the traditional Ga communities within the Accra metropolitan area.
  • C. Laak
    Laak is an urban district of The Hague in the Netherlands, known for its dense residential areas, canals, and diverse population.
  • D. Maasin
    Maasin is a coastal city in the Philippines that serves as the administrative, economic, and religious center of the province of Southern Leyte.
  • E. Lak
    Lak are a Northeast Caucasian ethnic group primarily inhabiting Dagestan in the North Caucasus region of Russia, known for their distinct Lak language and cultural traditions.
  • 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: لام
Triple: [Arabic Lām, nameInArabic, لام]
Generated description
لام هو الحرف الثالث والعشرون في الأبجدية العربية ويُستخدم لتمثيل صوت /l/ في اللغة العربية والعديد من اللغات الأخرى المكتوبة بالحرف العربي.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: لام
Target entity description: لام هو الحرف الثالث والعشرون في الأبجدية العربية ويُستخدم لتمثيل صوت /l/ في اللغة العربية والعديد من اللغات الأخرى المكتوبة بالحرف العربي.
  • A. Lagus
    Lagus was a Macedonian nobleman traditionally regarded as the father of Ptolemy I Soter, the founder of Egypt’s Ptolemaic dynasty.
  • B. La
    La is a coastal town in the Greater Accra Region of Ghana, known as one of the traditional Ga communities within the Accra metropolitan area.
  • C. Laak
    Laak is an urban district of The Hague in the Netherlands, known for its dense residential areas, canals, and diverse population.
  • D. Maasin
    Maasin is a coastal city in the Philippines that serves as the administrative, economic, and religious center of the province of Southern Leyte.
  • E. Lak
    Lak are a Northeast Caucasian ethnic group primarily inhabiting Dagestan in the North Caucasus region of Russia, known for their distinct Lak language and cultural traditions.
  • 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fd97d6c8190b2fa6ca422bfe512 completed April 16, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff83056aa0819098b757ed125e61fe completed May 9, 2026, 6:55 p.m.
NEDg Description generation batch_69ff83ca33d08190816130bf2ea735df completed May 9, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_69ff8469354c819080b8cfddb7c66be5 completed May 9, 2026, 7 p.m.
Created at: April 10, 2026, 4:46 a.m.