Triple

T14807161
Position Surface form Disambiguated ID Type / Status
Subject Little Odessa E348066 entity
Predicate musicBy P1952 FINISHED
Object Dana Sano
Dana Sano is a music professional best known for her work on the soundtrack of the film "Little Odessa."
E1120277 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: Dana Sano | Statement: [Little Odessa, musicBy, Dana Sano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dana Sano
Context triple: [Little Odessa, musicBy, Dana Sano]
  • A. Dana Dane
    Dana Dane is an American rapper and storyteller known for his humorous narrative style and influential 1980s hip-hop tracks like "Cinderfella Dana Dane."
  • B. Sol Yurick
    Sol Yurick was an American novelist and social critic best known for his 1965 gang novel "The Warriors," which was later adapted into the cult classic film of the same name.
  • C. Dana Lyon
    Dana Lyon was a writer whose work served as the basis for the film "The House on Telegraph Hill."
  • D. Danna
    Danna is the surname of Mychael Danna, a Canadian composer renowned for his innovative and atmospheric film scores.
  • E. Dana Natol
    Dana Natol was an American literary agent and film producer best known as the wife and professional partner of James Bond film producer Albert R. "Cubby" Broccoli.
  • 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: Dana Sano
Triple: [Little Odessa, musicBy, Dana Sano]
Generated description
Dana Sano is a music professional best known for her work on the soundtrack of the film "Little Odessa."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dana Sano
Target entity description: Dana Sano is a music professional best known for her work on the soundtrack of the film "Little Odessa."
  • A. Dana Dane
    Dana Dane is an American rapper and storyteller known for his humorous narrative style and influential 1980s hip-hop tracks like "Cinderfella Dana Dane."
  • B. Sol Yurick
    Sol Yurick was an American novelist and social critic best known for his 1965 gang novel "The Warriors," which was later adapted into the cult classic film of the same name.
  • C. Dana Lyon
    Dana Lyon was a writer whose work served as the basis for the film "The House on Telegraph Hill."
  • D. Danna
    Danna is the surname of Mychael Danna, a Canadian composer renowned for his innovative and atmospheric film scores.
  • E. Dana Natol
    Dana Natol was an American literary agent and film producer best known as the wife and professional partner of James Bond film producer Albert R. "Cubby" Broccoli.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decf33b6a08190ab6a4cfeda2cc09c completed April 14, 2026, 11:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24c8bc6881908736c029943997ae completed May 8, 2026, 6 p.m.
NEDg Description generation batch_69fe28222dc48190bca61ea273172950 completed May 8, 2026, 6:14 p.m.
NED2 Entity disambiguation (via description) batch_69fe28ba11a4819092e13669c53e6ecd completed May 8, 2026, 6:17 p.m.
Created at: April 10, 2026, 1:41 a.m.