Triple

T14100348
Position Surface form Disambiguated ID Type / Status
Subject Anápolis Air Base E339361 entity
Predicate abbreviation P43 FINISHED
Object BAAN
BAAN is the official abbreviation for Anápolis Air Base, a major Brazilian Air Force installation located in Anápolis, Goiás.
 E1080130 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: BAAN | Statement: [Anápolis Air Base, abbreviation, BAAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BAAN
Context triple: [Anápolis Air Base, abbreviation, BAAN]
  • A. BAAS
    BAAS is the acronym commonly used for the British Association for the Advancement of Science, a historic organization dedicated to promoting science and its understanding.
  • B. BAQ
    BAQ is the station code for Baquedano, a transit station in Chile’s transportation network.
  • C. БАН
    БАН is the Bulgarian abbreviation for the Bulgarian Academy of Sciences, the leading national institution for scientific research in Bulgaria.
  • D. BAA
    BAA is the acronym for the Basketball Association of America, the professional basketball league that later merged to form today’s National Basketball Association (NBA).
  • E. BAA
    BAA (formerly British Airports Authority) was a major UK airport operator that once managed several of the country’s largest airports, including Heathrow, Gatwick, and Stansted.
  • 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: BAAN
Triple: [Anápolis Air Base, abbreviation, BAAN]
Generated description
BAAN is the official abbreviation for Anápolis Air Base, a major Brazilian Air Force installation located in Anápolis, Goiás.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BAAN
Target entity description: BAAN is the official abbreviation for Anápolis Air Base, a major Brazilian Air Force installation located in Anápolis, Goiás.
  • A. BAAS
    BAAS is the acronym commonly used for the British Association for the Advancement of Science, a historic organization dedicated to promoting science and its understanding.
  • B. BAQ
    BAQ is the station code for Baquedano, a transit station in Chile’s transportation network.
  • C. БАН
    БАН is the Bulgarian abbreviation for the Bulgarian Academy of Sciences, the leading national institution for scientific research in Bulgaria.
  • D. BAA
    BAA is the acronym for the Basketball Association of America, the professional basketball league that later merged to form today’s National Basketball Association (NBA).
  • E. BAA
    BAA (formerly British Airports Authority) was a major UK airport operator that once managed several of the country’s largest airports, including Heathrow, Gatwick, and Stansted.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5fba7c10819095b1299b7b4f0310 completed April 14, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0b108908190b4b408f21ecb877a completed May 7, 2026, 5:49 p.m.
NEDg Description generation batch_69fcd5533dc88190b0ca6c0d7d47d84e completed May 7, 2026, 6:09 p.m.
NED2 Entity disambiguation (via description) batch_69fcd61f06e881909c3c42b83f858471 completed May 7, 2026, 6:12 p.m.
Created at: April 9, 2026, 10:22 p.m.