Triple

T7755563
Position Surface form Disambiguated ID Type / Status
Subject Our Gang E175887 entity
Predicate distributor P1951 FINISHED
Object Pathé Exchange
Pathé Exchange was an early 20th-century American film distribution company known for releasing popular silent comedies and serials.
 E114849 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: Pathé Exchange | Statement: [Our Gang, distributor, Pathé Exchange]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pathé Exchange
Context triple: [Our Gang, distributor, Pathé Exchange]
  • A. Pathé
    Pathé is a historic French film production and distribution company that also operated as a major record label in the early and mid-20th century.
  • B. Gaumont cinemas
    Gaumont cinemas is a historic French cinema chain known for operating movie theaters across France and being one of the oldest names in the film exhibition industry.
  • C. Cineplex Cinemas
    Cineplex Cinemas is a major Canadian movie theatre chain offering multiplex cinema experiences with multiple screens, concessions, and modern film presentation technologies.
  • D. Wanda Cinemas
    Wanda Cinemas is a major Chinese cinema chain known for operating a large network of modern movie theaters across China.
  • E. Regal Cinemas
    Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across the United States.
  • 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: Pathé Exchange
Triple: [Our Gang, distributor, Pathé Exchange]
Generated description
Pathé Exchange was an early 20th-century American film distribution company known for releasing popular silent comedies and serials.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pathé Exchange
Target entity description: Pathé Exchange was an early 20th-century American film distribution company known for releasing popular silent comedies and serials.
  • A. Pathé chosen
    Pathé is a historic French film production and distribution company that also operated as a major record label in the early and mid-20th century.
  • B. Gaumont cinemas
    Gaumont cinemas is a historic French cinema chain known for operating movie theaters across France and being one of the oldest names in the film exhibition industry.
  • C. Cineplex Cinemas
    Cineplex Cinemas is a major Canadian movie theatre chain offering multiplex cinema experiences with multiple screens, concessions, and modern film presentation technologies.
  • D. Wanda Cinemas
    Wanda Cinemas is a major Chinese cinema chain known for operating a large network of modern movie theaters across China.
  • E. Regal Cinemas
    Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across the United States.
  • 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_69c6996180088190832e38e8d83ff54a completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703d9d8fc8190b51faeb081ee425f completed March 27, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be5dbf5881908d07d70c8ae061a5 completed March 29, 2026, 5:53 a.m.
NEDg Description generation batch_69c8bfc8256081908a6ae947d783f19f completed March 29, 2026, 5:59 a.m.
NED2 Entity disambiguation (via description) batch_69c8c02e7a548190b2c5ad84e4c3f1fb completed March 29, 2026, 6:01 a.m.
Created at: March 27, 2026, 4:08 p.m.