Triple

T9293222
Position Surface form Disambiguated ID Type / Status
Subject Viridiana E223571 entity
Predicate distributor P1951 FINISHED
Object CIFESA
CIFESA was a major Spanish film production and distribution company, especially prominent during the mid-20th century.
 E789820 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: CIFESA | Statement: [Viridiana, distributor, CIFESA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CIFESA
Context triple: [Viridiana, distributor, CIFESA]
  • A. CESA
    CESA is a California state law that protects plant and animal species at risk of extinction by regulating activities that may harm them or their habitats.
  • B. FISC
    FISC is a specialized U.S. federal court that oversees and authorizes government requests for foreign intelligence surveillance, particularly in national security and counterterrorism cases.
  • C. ECASA
    ECASA is a Cuban state-owned company responsible for managing and operating the country’s civil airports and air terminals.
  • D. SICOFAA
    SICOFAA is a multinational military organization that coordinates cooperation, training, and mutual support among the air forces of countries in the Americas.
  • E. Cif
    Cif is a household cleaning product brand known for its creams and sprays used to remove tough dirt and stains from various surfaces.
  • 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: CIFESA
Triple: [Viridiana, distributor, CIFESA]
Generated description
CIFESA was a major Spanish film production and distribution company, especially prominent during the mid-20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CIFESA
Target entity description: CIFESA was a major Spanish film production and distribution company, especially prominent during the mid-20th century.
  • A. CESA
    CESA is a California state law that protects plant and animal species at risk of extinction by regulating activities that may harm them or their habitats.
  • B. FISC
    FISC is a specialized U.S. federal court that oversees and authorizes government requests for foreign intelligence surveillance, particularly in national security and counterterrorism cases.
  • C. ECASA
    ECASA is a Cuban state-owned company responsible for managing and operating the country’s civil airports and air terminals.
  • D. SICOFAA
    SICOFAA is a multinational military organization that coordinates cooperation, training, and mutual support among the air forces of countries in the Americas.
  • E. Cif
    Cif is a household cleaning product brand known for its creams and sprays used to remove tough dirt and stains from various surfaces.
  • 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_69ca8422ddf881908a3f8f876c9f53aa completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd0898b3288190a627a58bfd9c57fe completed April 1, 2026, 11:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0b241251c81909aa4e8bcf5cd9c2e completed April 4, 2026, 6:40 a.m.
NEDg Description generation batch_69d0b3324e7c8190b928928bbfbdbadf completed April 4, 2026, 6:44 a.m.
NED2 Entity disambiguation (via description) batch_69d0b3d40da08190b25118a0901728da completed April 4, 2026, 6:46 a.m.
Created at: March 30, 2026, 7:35 p.m.