Triple

T10629034
Position Surface form Disambiguated ID Type / Status
Subject Tuanku Muhriz E250402 entity
Predicate givenName P17 FINISHED
Object Muhriz
Muhriz is the given name of Tuanku Muhriz, the reigning Yang di-Pertuan Besar (ruler) of the Malaysian state of Negeri Sembilan.
 E875736 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: Muhriz | Statement: [Tuanku Muhriz, givenName, Muhriz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Muhriz
Context triple: [Tuanku Muhriz, givenName, Muhriz]
  • A. Guzan
    Guzan is the surname of American professional soccer goalkeeper Brad Guzan, known for his career in Major League Soccer and the U.S. national team.
  • B. Faifi
    Faifi is a modern South Arabian language variety spoken by the Faifi people in the mountainous Jazan region of southwestern Saudi Arabia.
  • C. Mazuelo
    Mazuelo is a red wine grape variety, better known internationally as Carignan, used primarily in blends for its high acidity, color, and tannins.
  • D. Mirza
    Mirza is a historical noble title of Persian and Central Asian origin, commonly borne by princes and high-ranking members of royal and aristocratic families.
  • E. Muazzez
    Muazzez is a Turkish feminine given name borne by several notable women, including the prominent Sumerologist Muazzez İlmiye Çığ.
  • 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: Muhriz
Triple: [Tuanku Muhriz, givenName, Muhriz]
Generated description
Muhriz is the given name of Tuanku Muhriz, the reigning Yang di-Pertuan Besar (ruler) of the Malaysian state of Negeri Sembilan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Muhriz
Target entity description: Muhriz is the given name of Tuanku Muhriz, the reigning Yang di-Pertuan Besar (ruler) of the Malaysian state of Negeri Sembilan.
  • A. Guzan
    Guzan is the surname of American professional soccer goalkeeper Brad Guzan, known for his career in Major League Soccer and the U.S. national team.
  • B. Faifi
    Faifi is a modern South Arabian language variety spoken by the Faifi people in the mountainous Jazan region of southwestern Saudi Arabia.
  • C. Mazuelo
    Mazuelo is a red wine grape variety, better known internationally as Carignan, used primarily in blends for its high acidity, color, and tannins.
  • D. Mirza
    Mirza is a historical noble title of Persian and Central Asian origin, commonly borne by princes and high-ranking members of royal and aristocratic families.
  • E. Muazzez
    Muazzez is a Turkish feminine given name borne by several notable women, including the prominent Sumerologist Muazzez İlmiye Çığ.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df92f8388190a8bcff96809d8eb4 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96babc290819096c0c914d038ba01 completed April 10, 2026, 9:29 p.m.
NEDg Description generation batch_69d96def8bfc81909d6a5addf724691b completed April 10, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_69d96fedb18881908570593856f4aade completed April 10, 2026, 9:47 p.m.
Created at: April 8, 2026, 8:59 p.m.