Triple

T13310566
Position Surface form Disambiguated ID Type / Status
Subject Simon Chinn E317049 entity
Predicate employer P7 FINISHED
Object Red Box Films E1033216 NE FINISHED

How this triple was built (2 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: Red Box Films | Statement: [Simon Chinn, employer, Red Box Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red Box Films
Context triple: [Simon Chinn, employer, Red Box Films]
  • A. Red Box Films chosen
    Red Box Films is a British film production company best known for producing acclaimed feature documentaries, including several award-winning works.
  • B. Reel Mall
    Reel Mall is a prominent upscale shopping and lifestyle center located in Shanghai’s central Jing’an District.
  • C. Blockbuster Video
    Blockbuster Video was a once-dominant American home video rental chain known for its widespread brick-and-mortar stores and iconic blue-and-yellow branding before largely disappearing with the rise of digital streaming.
  • D. Beyond Films
    Beyond Films is an Australian film distribution and production company known for handling a range of independent and international titles.
  • E. Reel Cinemas
    Reel Cinemas is a popular cinema chain in Dubai known for its modern multiplex theaters and premium movie-going experiences.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f56abc8190951774a999e2ce11 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f2810a881908b1ed0cc4fb9ac12 completed May 3, 2026, 10:10 a.m.
Created at: April 9, 2026, 9:29 p.m.