Triple

T10672715
Position Surface form Disambiguated ID Type / Status
Subject iRobot E251534 entity
Predicate notableProduct P1448 FINISHED
Object Mirra
Mirra is an iRobot-designed robotic pool cleaner that autonomously scrubs and vacuums swimming pools.
 E879758 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: Mirra | Statement: [iRobot, notableProduct, Mirra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mirra
Context triple: [iRobot, notableProduct, Mirra]
  • A. Mila
    Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
  • B. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • C. Nadya
    Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
  • D. Ludmila
    Ludmila is the heroine of Alexander Pushkin’s narrative poem "Ruslan and Ludmila," known as a beautiful Kievan princess whose abduction sets the story’s adventurous plot in motion.
  • E. Zhanna
    Zhanna is a feminine given name commonly used in Russian and other Slavic cultures, equivalent to Jeanne or Joanna.
  • 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: Mirra
Triple: [iRobot, notableProduct, Mirra]
Generated description
Mirra is an iRobot-designed robotic pool cleaner that autonomously scrubs and vacuums swimming pools.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mirra
Target entity description: Mirra is an iRobot-designed robotic pool cleaner that autonomously scrubs and vacuums swimming pools.
  • A. Mila
    Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
  • B. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • C. Nadya
    Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
  • D. Ludmila
    Ludmila is the heroine of Alexander Pushkin’s narrative poem "Ruslan and Ludmila," known as a beautiful Kievan princess whose abduction sets the story’s adventurous plot in motion.
  • E. Zhanna
    Zhanna is a feminine given name commonly used in Russian and other Slavic cultures, equivalent to Jeanne or Joanna.
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6f8659d40819087a2709bd24261ee completed April 9, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9886e3f108190bb6f17d4e2f394ef completed April 10, 2026, 11:31 p.m.
NEDg Description generation batch_69d98cdf6f0c8190a5b926c439c1aca6 completed April 10, 2026, 11:50 p.m.
NED2 Entity disambiguation (via description) batch_69d98d5557548190a22102f1c8105e6f completed April 10, 2026, 11:52 p.m.
Created at: April 8, 2026, 9:09 p.m.