Triple

T9449945
Position Surface form Disambiguated ID Type / Status
Subject Jordan Vogt-Roberts E227860 entity
Predicate directorOf P537 FINISHED
Object Mash Up
Mash Up is a television sketch comedy series directed by filmmaker Jordan Vogt-Roberts.
 E799009 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: Mash Up | Statement: [Jordan Vogt-Roberts, directorOf, Mash Up]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mash Up
Context triple: [Jordan Vogt-Roberts, directorOf, Mash Up]
  • A. The Mix
    The Mix is a UK-based digital support service offering free, confidential help and counseling for young people facing mental health, relationship, and life challenges.
  • B. In the Mix
    In the Mix is a 2005 romantic comedy-crime film starring Usher as a DJ who becomes a bodyguard entangled in a mob family's affairs.
  • C. Le Grand Mix
    Le Grand Mix is a renowned live music venue and cultural hub in Tourcoing, France, known for hosting diverse contemporary music performances and events.
  • D. MIX
    MIX is Donald Knuth’s hypothetical computer architecture used in *The Art of Computer Programming* to illustrate and analyze algorithms in a machine-level context.
  • E. Jhankaar Beats
    Jhankaar Beats is a 2003 Hindi musical comedy film known for its tribute to R.D. Burman, its popular soundtrack, and its story of three friends forming a band.
  • 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: Mash Up
Triple: [Jordan Vogt-Roberts, directorOf, Mash Up]
Generated description
Mash Up is a television sketch comedy series directed by filmmaker Jordan Vogt-Roberts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mash Up
Target entity description: Mash Up is a television sketch comedy series directed by filmmaker Jordan Vogt-Roberts.
  • A. The Mix
    The Mix is a UK-based digital support service offering free, confidential help and counseling for young people facing mental health, relationship, and life challenges.
  • B. In the Mix
    In the Mix is a 2005 romantic comedy-crime film starring Usher as a DJ who becomes a bodyguard entangled in a mob family's affairs.
  • C. Le Grand Mix
    Le Grand Mix is a renowned live music venue and cultural hub in Tourcoing, France, known for hosting diverse contemporary music performances and events.
  • D. MIX
    MIX is Donald Knuth’s hypothetical computer architecture used in *The Art of Computer Programming* to illustrate and analyze algorithms in a machine-level context.
  • E. Jhankaar Beats
    Jhankaar Beats is a 2003 Hindi musical comedy film known for its tribute to R.D. Burman, its popular soundtrack, and its story of three friends forming a band.
  • 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_69ca8439f8bc8190997f2ef40c9f0bc2 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7f6649a48190b6844daa6202efe5 completed April 1, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1106f38448190bfdc289eb987e33f completed April 4, 2026, 1:21 p.m.
NEDg Description generation batch_69d110eeddc881908661d110269b8a1c completed April 4, 2026, 1:23 p.m.
NED2 Entity disambiguation (via description) batch_69d111f4b7048190977a7cca6a4247f0 completed April 4, 2026, 1:28 p.m.
Created at: March 30, 2026, 7:51 p.m.