Triple

T3064999
Position Surface form Disambiguated ID Type / Status
Subject Mona Simpson E62082 entity
Predicate givenName P17 FINISHED
Object Mona
Mona is a feminine given name used in various cultures, often as a standalone name or a diminutive of names like Ramona or Simona.
E323562 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: Mona | Statement: [Mona Simpson, givenName, Mona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mona
Context triple: [Mona Simpson, givenName, Mona]
  • A. MONA
    MONA is a renowned private art museum in Hobart, Tasmania, known for its provocative contemporary and ancient art collections and unconventional, immersive visitor experience.
  • B. Pauletta
    Pauletta is a feminine given name, typically considered a diminutive or variant of Paula or Pauline.
  • C. Mella
    Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
  • D. Mylasa
    Mylasa was an important ancient city of Caria in southwestern Anatolia, known as a political and religious center, particularly for the worship of Zeus.
  • E. Tihamah
    Tihamah is a low-lying coastal plain along the Red Sea in western Arabia, known historically as a hot, arid region encompassing parts of modern-day Saudi Arabia and Yemen.
  • 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: Mona
Triple: [Mona Simpson, givenName, Mona]
Generated description
Mona is a feminine given name used in various cultures, often as a standalone name or a diminutive of names like Ramona or Simona.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mona
Target entity description: Mona is a feminine given name used in various cultures, often as a standalone name or a diminutive of names like Ramona or Simona.
  • A. MONA
    MONA is a renowned private art museum in Hobart, Tasmania, known for its provocative contemporary and ancient art collections and unconventional, immersive visitor experience.
  • B. Pauletta
    Pauletta is a feminine given name, typically considered a diminutive or variant of Paula or Pauline.
  • C. Mella
    Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
  • D. Mylasa
    Mylasa was an important ancient city of Caria in southwestern Anatolia, known as a political and religious center, particularly for the worship of Zeus.
  • E. Amonute
    Amonute is one of the lesser-known names of Pocahontas, the Native American woman famous for her association with the early English colonial settlement at Jamestown, Virginia.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada0fc01dc81908fbdf7c1ef73afe4 completed March 8, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef1402108190a2d24e7eb523f658 completed March 11, 2026, 10:39 p.m.
NEDg Description generation batch_69b1f2f3d120819090d28e0353d3d8da completed March 11, 2026, 10:55 p.m.
NED2 Entity disambiguation (via description) batch_69b1f365a4988190ae3ea6370a27ee72 completed March 11, 2026, 10:57 p.m.
Created at: March 8, 2026, 3:02 p.m.