Triple

T9911390
Position Surface form Disambiguated ID Type / Status
Subject KAA Gent E185151 entity
Predicate usesAbbreviation P43 FINISHED
Object KAA
KAA is the commonly used abbreviation for K.A.A. Gent, a professional football club based in Ghent, Belgium.
 E829625 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: KAA | Statement: [KAA Gent, usesAbbreviation, KAA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KAA
Context triple: [KAA Gent, usesAbbreviation, KAA]
  • A. KAA
    KAA is the state corporation responsible for managing and operating Kenya’s civil airports and airstrips.
  • B. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • C. KAU
    KAU is the IATA airport code for Kauhava Air Base, a former military airfield in Kauhava, Finland.
  • D. KCA
    KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
  • E. KAIA
    KAIA is a major international airport in Jeddah, Saudi Arabia, serving as a key gateway for pilgrims traveling to the holy cities of Mecca and Medina.
  • 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: KAA
Triple: [KAA Gent, usesAbbreviation, KAA]
Generated description
KAA is the commonly used abbreviation for K.A.A. Gent, a professional football club based in Ghent, Belgium.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KAA
Target entity description: KAA is the commonly used abbreviation for K.A.A. Gent, a professional football club based in Ghent, Belgium.
  • A. KAA
    KAA is the state corporation responsible for managing and operating Kenya’s civil airports and airstrips.
  • B. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • C. KAU
    KAU is the IATA airport code for Kauhava Air Base, a former military airfield in Kauhava, Finland.
  • D. KCA
    KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
  • E. KAIA
    KAIA is a major international airport in Jeddah, Saudi Arabia, serving as a key gateway for pilgrims traveling to the holy cities of Mecca and Medina.
  • 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb512a26881908eb72a21ffb1efef completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20dbfa89881909ea6bbcfcf6fc08f completed April 5, 2026, 7:22 a.m.
NEDg Description generation batch_69d20ed1f69c819099faa881a9a4368d completed April 5, 2026, 7:27 a.m.
NED2 Entity disambiguation (via description) batch_69d212e3b864819092b8464f5a5ab696 completed April 5, 2026, 7:44 a.m.
Created at: March 30, 2026, 8:41 p.m.