Triple

T10482899
Position Surface form Disambiguated ID Type / Status
Subject Portuguese culture E247215 entity
Predicate hasMedia P7961 FINISHED
Object SIC
SIC is a major Portuguese television network known for its wide range of entertainment, news, and cultural programming.
 E864848 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: SIC | Statement: [Portuguese culture, hasMedia, SIC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SIC
Context triple: [Portuguese culture, hasMedia, SIC]
  • A. SICA
    SICA is a regional organization that promotes political, economic, and social integration among Central American countries.
  • B. CIC
    CIC is the three-letter IATA airport code assigned to Chico Municipal Airport in Chico, California.
  • C. CIC
    CIC is the commonly used abbreviation for the Cement Industry Committee, an organization associated with the cement sector.
  • D. SIS
    SIS is the CERN Scientific Information Service, responsible for managing and providing access to the organization’s scientific publications, data, and library resources.
  • E. SIS
    SIS is the commonly used abbreviation for the United Kingdom’s Secret Intelligence Service, the foreign intelligence agency often referred to as MI6.
  • 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: SIC
Triple: [Portuguese culture, hasMedia, SIC]
Generated description
SIC is a major Portuguese television network known for its wide range of entertainment, news, and cultural programming.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SIC
Target entity description: SIC is a major Portuguese television network known for its wide range of entertainment, news, and cultural programming.
  • A. SICA
    SICA is a regional organization that promotes political, economic, and social integration among Central American countries.
  • B. CIC
    CIC is the three-letter IATA airport code assigned to Chico Municipal Airport in Chico, California.
  • C. CIC
    CIC is the commonly used abbreviation for the Cement Industry Committee, an organization associated with the cement sector.
  • D. SIS
    SIS is the CERN Scientific Information Service, responsible for managing and providing access to the organization’s scientific publications, data, and library resources.
  • E. SIS
    SIS is the commonly used abbreviation for the United Kingdom’s Secret Intelligence Service, the foreign intelligence agency often referred to as MI6.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5095d21c08190a0b2f3e57fabb1d8 completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8a03336988190bc1e61126fe576be completed April 10, 2026, 7:01 a.m.
NEDg Description generation batch_69d8a166404881909c28141fefea2936 completed April 10, 2026, 7:06 a.m.
NED2 Entity disambiguation (via description) batch_69d8a2c550ac81908444c6abfe14698a completed April 10, 2026, 7:12 a.m.
Created at: April 6, 2026, 12:22 p.m.