Triple

T7232482
Position Surface form Disambiguated ID Type / Status
Subject Slovenian Academy of Sciences and Arts E154935 entity
Predicate abbreviation P43 FINISHED
Object SAZU
SAZU is the national academy of sciences and arts of Slovenia, serving as the country’s leading scholarly and artistic institution.
 E650451 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: SAZU | Statement: [Slovenian Academy of Sciences and Arts, abbreviation, SAZU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SAZU
Context triple: [Slovenian Academy of Sciences and Arts, abbreviation, SAZU]
  • A. SAZS
    SAZS is the ICAO airport code for San Carlos de Bariloche Airport, a major gateway to the Patagonia region of Argentina.
  • B. Sanz
    Sanz is a prominent Hasidic dynasty known for its strong emphasis on Torah scholarship, strict halachic observance, and influential rabbinic leadership originating in 19th-century Galicia.
  • C. AZU
    AZU is the ICAO airline designator for Azul Brazilian Airlines, a major low-cost carrier based in Brazil.
  • D. ZAZ
    ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
  • E. Shizaf
    Shizaf is a small community settlement in Israel’s Negev desert, known for its rural character and location within the Ramat Negev region.
  • 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: SAZU
Triple: [Slovenian Academy of Sciences and Arts, abbreviation, SAZU]
Generated description
SAZU is the national academy of sciences and arts of Slovenia, serving as the country’s leading scholarly and artistic institution.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SAZU
Target entity description: SAZU is the national academy of sciences and arts of Slovenia, serving as the country’s leading scholarly and artistic institution.
  • A. SAZS
    SAZS is the ICAO airport code for San Carlos de Bariloche Airport, a major gateway to the Patagonia region of Argentina.
  • B. Sanz
    Sanz is a prominent Hasidic dynasty known for its strong emphasis on Torah scholarship, strict halachic observance, and influential rabbinic leadership originating in 19th-century Galicia.
  • C. AZU
    AZU is the ICAO airline designator for Azul Brazilian Airlines, a major low-cost carrier based in Brazil.
  • D. ZAZ
    ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
  • E. Shizaf
    Shizaf is a small community settlement in Israel’s Negev desert, known for its rural character and location within the Ramat Negev region.
  • 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_69c68811dd1c8190ac460bb39e64e1f0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea106cc881909348be576ced4beb completed March 27, 2026, 8:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc2786f88190b0008891f801ca95 completed March 28, 2026, 12:40 p.m.
NEDg Description generation batch_69c7cd7cb5f081908c2ca7ce8653f25f completed March 28, 2026, 12:45 p.m.
NED2 Entity disambiguation (via description) batch_69c7cdf9e0608190a466ed638b728924 completed March 28, 2026, 12:47 p.m.
Created at: March 27, 2026, 2:54 p.m.