Triple

T20010809
Position Surface form Disambiguated ID Type / Status
Subject The Professor's gang E494583 entity
Predicate hasMember P10 FINISHED
Object Rio
Rio is a young, talented hacker and member of the central heist crew in the Spanish television series "Money Heist" (La Casa de Papel).
E144475 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: Rio | Statement: [The Professor's gang, hasMember, Rio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rio
Context triple: [The Professor's gang, hasMember, Rio]
  • A. Rio
    "Rio" is a song featured on Mika's album "No Place in Heaven."
  • B. Rio
    Rio is a masculine given name used in various cultures, often associated with the Spanish and Portuguese word for "river" and popularized by figures in sports and entertainment.
  • C. Rio
    "Rio" is a notable work by Harry Hitner, recognized as one of his significant creative contributions.
  • D. Rio
    Rio is a creative work associated with Todd R. Jones, likely a notable project or production that contributed to his recognition.
  • E. Rio
    Rio is a section of the Brazilian newspaper O Globo that focuses on news, events, and issues related to the city of Rio de Janeiro.
  • 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: Rio
Triple: [The Professor's gang, hasMember, Rio]
Generated description
Rio is a young, talented hacker and member of the central heist crew in the Spanish television series "Money Heist" (La Casa de Papel).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rio
Target entity description: Rio is a young, talented hacker and member of the central heist crew in the Spanish television series "Money Heist" (La Casa de Papel).
  • A. Rio chosen
    Rio is a young, talented hacker and one of the central robbers in the Spanish television series "Money Heist" (La Casa de Papel).
  • B. Rio
    Rio is a masculine given name used in various cultures, often associated with the Spanish and Portuguese word for "river" and popularized by figures in sports and entertainment.
  • C. Rio
    Rio is a section of the Brazilian newspaper O Globo that focuses on news, events, and issues related to the city of Rio de Janeiro.
  • D. Rio
    Rio is a creative work, likely a film or artistic project, associated with Jenico Damasco.
  • E. Rio
    Rio is a 2011 animated adventure-comedy film set in Brazil that follows a domesticated macaw’s journey of self-discovery amid vibrant music and colorful Rio de Janeiro scenery.
  • F. None of above.

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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662362df48190abf16129eea39985 completed April 20, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a080e17a53c8190b3f0957ded38bd5d completed May 16, 2026, 6:26 a.m.
NEDg Description generation batch_6a080fcaa49881908016c87f2aeb880f completed May 16, 2026, 6:33 a.m.
NED2 Entity disambiguation (via description) batch_6a0813a9147c8190ad9f98ab36b363e2 completed May 16, 2026, 6:50 a.m.
Created at: April 11, 2026, 3:33 p.m.