Triple

T8035818
Position Surface form Disambiguated ID Type / Status
Subject Seal IV E187103 entity
Predicate hasPart P35 FINISHED
Object “Tinsel Town”
“Tinsel Town” is a track by the rapper Seal IV, featured as part of his musical work.
 E708912 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: “Tinsel Town” | Statement: [Seal IV, hasPart, “Tinsel Town”]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: “Tinsel Town”
Context triple: [Seal IV, hasPart, “Tinsel Town”]
  • A. Tinseltown USA
    Tinseltown USA is a movie theater brand operated by Cinemark Theatres, known for its multiplex cinemas offering mainstream film screenings.
  • B. Hollywood
    Hollywood is a residential neighborhood in the city of College Park, Maryland, known for its suburban character and proximity to the University of Maryland.
  • C. Hollywood
    Hollywood is a residential neighborhood in Homewood, Alabama, known for its historic homes and suburban character just outside Birmingham.
  • D. Hollywood
    Hollywood is a famous Los Angeles neighborhood internationally recognized as the historic center of the American film and entertainment industry.
  • E. Hollywood
    Hollywood is a coastal city in southeastern Florida known for its beaches, boardwalk, and proximity to Miami.
  • 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: “Tinsel Town”
Triple: [Seal IV, hasPart, “Tinsel Town”]
Generated description
“Tinsel Town” is a track by the rapper Seal IV, featured as part of his musical work.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: “Tinsel Town”
Target entity description: “Tinsel Town” is a track by the rapper Seal IV, featured as part of his musical work.
  • A. Tinseltown USA
    Tinseltown USA is a movie theater brand operated by Cinemark Theatres, known for its multiplex cinemas offering mainstream film screenings.
  • B. Hollywood
    Hollywood is a residential neighborhood in the city of College Park, Maryland, known for its suburban character and proximity to the University of Maryland.
  • C. Hollywood
    Hollywood is a residential neighborhood in Homewood, Alabama, known for its historic homes and suburban character just outside Birmingham.
  • D. Hollywood
    Hollywood is a famous Los Angeles neighborhood internationally recognized as the historic center of the American film and entertainment industry.
  • E. Hollywood
    Hollywood is a coastal city in southeastern Florida known for its beaches, boardwalk, and proximity to Miami.
  • 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_69ca82ae2d1081909dbfee42b41db419 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ef68c6081908727d17238b3522a completed March 31, 2026, 3:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56f493908190b68e791cdbe725fa completed March 31, 2026, 11:21 p.m.
NEDg Description generation batch_69cc5ca6efbc819082f4c643446da354 completed March 31, 2026, 11:45 p.m.
NED2 Entity disambiguation (via description) batch_69cc5d6d93f08190b17d6c7a4fad2cf0 completed March 31, 2026, 11:49 p.m.
Created at: March 30, 2026, 5:22 p.m.