Triple

T11310031
Position Surface form Disambiguated ID Type / Status
Subject Bunkachō E267812 entity
Predicate abbreviation P43 FINISHED
Object ACA
ACA is the commonly used English abbreviation for Japan’s Agency for Cultural Affairs, the government body responsible for cultural policy and heritage protection.
E917348 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: ACA | Statement: [Bunkachō, abbreviation, ACA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ACA
Context triple: [Bunkachō, abbreviation, ACA]
  • A. ACA
    ACA is the three-letter ICAO airline designator used to identify Air Canada in international aviation operations and communications.
  • B. ACA
    ACA is a professional scientific organization that promotes the study and application of crystallography and structural science, primarily in North America.
  • C. ACA
    ACA is the common abbreviation for the Affordable Care Act, a major U.S. health care reform law enacted in 2010 to expand insurance coverage and consumer protections.
  • D. ACA
    ACA is a subset of the Atacama Large Millimeter/submillimeter Array (ALMA) consisting of closely spaced radio telescopes designed to improve imaging of extended astronomical objects.
  • E. ACA
    ACA is the acronym commonly used for the Army Comrades Association, an Irish nationalist organization active in the early 20th century.
  • 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: ACA
Triple: [Bunkachō, abbreviation, ACA]
Generated description
ACA is the commonly used English abbreviation for Japan’s Agency for Cultural Affairs, the government body responsible for cultural policy and heritage protection.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: ACA
Target entity description: ACA is the commonly used English abbreviation for Japan’s Agency for Cultural Affairs, the government body responsible for cultural policy and heritage protection.
  • A. ACA
    ACA is the three-letter ICAO airline designator used to identify Air Canada in international aviation operations and communications.
  • B. ACA
    ACA is the acronym commonly used for the Army Comrades Association, an Irish nationalist organization active in the early 20th century.
  • C. ACA
    ACA is the common abbreviation for the Affordable Care Act, a major U.S. health care reform law enacted in 2010 to expand insurance coverage and consumer protections.
  • D. ACA
    ACA is a professional scientific organization that promotes the study and application of crystallography and structural science, primarily in North America.
  • E. ACA
    ACA is the IATA airport code for Acapulco International Airport, the main air gateway serving Acapulco, Mexico.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e50a7fc06881909afe85a600d25ff2 completed April 19, 2026, 5:01 p.m.
NEDg Description generation batch_69e510fb1e288190a7a38fe896d7b91d completed April 19, 2026, 5:29 p.m.
NED2 Entity disambiguation (via description) batch_69e516d0910481908fee176db0d9229b completed April 19, 2026, 5:54 p.m.
Created at: April 8, 2026, 9:32 p.m.