Triple

T13983178
Position Surface form Disambiguated ID Type / Status
Subject Return to Sender E336365 entity
Predicate protagonist P268 FINISHED
Object Mari
Mari is the central character of the film "Return to Sender," around whom the story’s psychological drama and suspense unfold.
 E1074140 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: Mari | Statement: [Return to Sender, protagonist, Mari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mari
Context triple: [Return to Sender, protagonist, Mari]
  • A. Mari
    Mari is a character in Paulo Coelho's novel "Veronika Decides to Die," portrayed as a fellow patient in the mental institution who struggles with anxiety and societal expectations.
  • B. Mari
    Mari is a Uralic language spoken by the Mari people, primarily in the Mari El Republic of Russia.
  • C. Mari
    Mari is an ancient Mesopotamian city-state on the Euphrates River, renowned for its well-preserved palace complex and thousands of cuneiform tablets that illuminate early Syrian and Mesopotamian history.
  • D. Mari
    Mari is a feminine given name, often used as a short form of names like Marigold, Mary, or Maria in various cultures.
  • E. Marla
    Marla is a feminine given name most notably borne by American actress and television personality Marla Maples.
  • 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: Mari
Triple: [Return to Sender, protagonist, Mari]
Generated description
Mari is the central character of the film "Return to Sender," around whom the story’s psychological drama and suspense unfold.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mari
Target entity description: Mari is the central character of the film "Return to Sender," around whom the story’s psychological drama and suspense unfold.
  • A. Mari
    Mari is a character in Paulo Coelho's novel "Veronika Decides to Die," portrayed as a fellow patient in the mental institution who struggles with anxiety and societal expectations.
  • B. Mari
    Mari is a Uralic language spoken by the Mari people, primarily in the Mari El Republic of Russia.
  • C. Mari
    Mari is an ancient Mesopotamian city-state on the Euphrates River, renowned for its well-preserved palace complex and thousands of cuneiform tablets that illuminate early Syrian and Mesopotamian history.
  • D. Mari
    Mari is a feminine given name, often used as a short form of names like Marigold, Mary, or Maria in various cultures.
  • E. Marla
    Marla is a feminine given name most notably borne by American actress and television personality Marla Maples.
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ea2e8808190a1203a6386224bd8 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac9231888190ad8cb460db73bdb4 completed May 6, 2026, 9:03 p.m.
NEDg Description generation batch_69fbaf8dc2088190bd69f760ff15c03d completed May 6, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_69fbb01071408190a85e5e9be0150593 completed May 6, 2026, 9:18 p.m.
Created at: April 9, 2026, 10:18 p.m.