Triple

T13182787
Position Surface form Disambiguated ID Type / Status
Subject Bulgarian Academy of Sciences E313770 entity
Predicate nativeShortName P657 FINISHED
Object БАН
БАН is the Bulgarian abbreviation for the Bulgarian Academy of Sciences, the leading national institution for scientific research in Bulgaria.
E1026741 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: БАН | Statement: [Bulgarian Academy of Sciences, nativeShortName, БАН]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: БАН
Context triple: [Bulgarian Academy of Sciences, nativeShortName, БАН]
  • A. Bankan Tey
    Bankan Tey is a Dogon language variety spoken by the Dogon people of Mali in West Africa.
  • B. BNK
    BNK is the IATA airport code for Ballina Byron Gateway Airport, a regional airport serving the Ballina and Byron Bay areas in New South Wales, Australia.
  • C. BAN
    BAN is the National Rail station code for Banbury railway station in Oxfordshire, England.
  • D. BNM
    BNM is the central bank of Malaysia, responsible for issuing currency, formulating monetary policy, and overseeing the country’s financial system.
  • E. Bankal
    Bankal is a Jarawan Bantu language spoken by a small ethnic community in Nigeria.
  • 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: БАН
Triple: [Bulgarian Academy of Sciences, nativeShortName, БАН]
Generated description
БАН is the Bulgarian abbreviation for the Bulgarian Academy of Sciences, the leading national institution for scientific research in Bulgaria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: БАН
Target entity description: БАН is the Bulgarian abbreviation for the Bulgarian Academy of Sciences, the leading national institution for scientific research in Bulgaria.
  • A. Bankan Tey
    Bankan Tey is a Dogon language variety spoken by the Dogon people of Mali in West Africa.
  • B. BNK
    BNK is the IATA airport code for Ballina Byron Gateway Airport, a regional airport serving the Ballina and Byron Bay areas in New South Wales, Australia.
  • C. BAN
    BAN is the National Rail station code for Banbury railway station in Oxfordshire, England.
  • D. BNM
    BNM is the central bank of Malaysia, responsible for issuing currency, formulating monetary policy, and overseeing the country’s financial system.
  • E. Bankal
    Bankal is a Jarawan Bantu language spoken by a small ethnic community in Nigeria.
  • 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c4a0b0081908027bf77442ff5ff completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5f307408190afd0df16a417c456 completed May 3, 2026, 7:14 a.m.
NEDg Description generation batch_69f6f707d9e48190b772520ca9f4ac2c completed May 3, 2026, 7:19 a.m.
NED2 Entity disambiguation (via description) batch_69f6f8530a048190b448c50bfa52c057 completed May 3, 2026, 7:25 a.m.
Created at: April 9, 2026, 9:15 p.m.