Triple

T10648216
Position Surface form Disambiguated ID Type / Status
Subject Mena Massoud E250891 entity
Predicate givenName P17 FINISHED
Object Mena
Mena is a masculine given name of Arabic origin, commonly used in Middle Eastern and North African cultures.
 E877151 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: Mena | Statement: [Mena Massoud, givenName, Mena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mena
Context triple: [Mena Massoud, givenName, Mena]
  • A. Mena
    Mena is a small town located in northern Ukraine’s Chernihiv region, known for its rural character and local agricultural activities.
  • B. Nedra
    "Nedra" is a romantic adventure novel by American author George Barr McCutcheon, best known for its shipwreck narrative and themes of love and survival.
  • C. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • D. Mia Ausa
    Mia Ausa is a young, kind-hearted magician and the daughter of the Magic Guild's leader in the role-playing game Lunar: The Silver Star.
  • E. Lyonne
    Lyonne is the surname of American actress, writer, director, and producer Natasha Lyonne, known for her roles in "Orange Is the New Black" and "Russian Doll."
  • 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: Mena
Triple: [Mena Massoud, givenName, Mena]
Generated description
Mena is a masculine given name of Arabic origin, commonly used in Middle Eastern and North African cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mena
Target entity description: Mena is a masculine given name of Arabic origin, commonly used in Middle Eastern and North African cultures.
  • A. Mena
    Mena is a small town located in northern Ukraine’s Chernihiv region, known for its rural character and local agricultural activities.
  • B. Nedra
    "Nedra" is a romantic adventure novel by American author George Barr McCutcheon, best known for its shipwreck narrative and themes of love and survival.
  • C. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • D. Mia Ausa
    Mia Ausa is a young, kind-hearted magician and the daughter of the Magic Guild's leader in the role-playing game Lunar: The Silver Star.
  • E. Lyonne
    Lyonne is the surname of American actress, writer, director, and producer Natasha Lyonne, known for her roles in "Orange Is the New Black" and "Russian Doll."
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfe29b8081908eb13637e0475ba1 completed April 8, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a60fdd881908987f920a19bb41e completed April 10, 2026, 10:32 p.m.
NEDg Description generation batch_69d97cc20448819094d650b9c1067dca completed April 10, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69d97e13913081908dd1fb60fa44db05 completed April 10, 2026, 10:47 p.m.
Created at: April 8, 2026, 9:05 p.m.