Triple

T12386072
Position Surface form Disambiguated ID Type / Status
Subject Kolkata Metropolitan Area E295867 entity
Predicate shortName P43 FINISHED
Object KMA
KMA is the commonly used abbreviation for the Kolkata Metropolitan Area, a major urban agglomeration centered on the city of Kolkata in eastern India.
 E979413 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: KMA | Statement: [Kolkata Metropolitan Area, shortName, KMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KMA
Context triple: [Kolkata Metropolitan Area, shortName, KMA]
  • A. KMA
    KMA is the commonly used abbreviation for the Royal Swedish Academy of Music, Sweden’s national institution dedicated to the advancement of musical art and scholarship.
  • B. KAM
    KAM is the standard abbreviation for the Kamloops Blazers, a major junior ice hockey team in the Western Hockey League based in Kamloops, British Columbia.
  • C. KMF
    KMF is the ISO 4217 currency code for the Comorian franc, the official monetary unit of the Comoros.
  • D. KMSKA
    KMSKA is the Royal Museum of Fine Arts in Antwerp, renowned for its extensive collection of Flemish and Belgian art spanning several centuries.
  • E. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • 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: KMA
Triple: [Kolkata Metropolitan Area, shortName, KMA]
Generated description
KMA is the commonly used abbreviation for the Kolkata Metropolitan Area, a major urban agglomeration centered on the city of Kolkata in eastern India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KMA
Target entity description: KMA is the commonly used abbreviation for the Kolkata Metropolitan Area, a major urban agglomeration centered on the city of Kolkata in eastern India.
  • A. KMA
    KMA is the commonly used abbreviation for the Royal Swedish Academy of Music, Sweden’s national institution dedicated to the advancement of musical art and scholarship.
  • B. KAM
    KAM is the standard abbreviation for the Kamloops Blazers, a major junior ice hockey team in the Western Hockey League based in Kamloops, British Columbia.
  • C. KMF
    KMF is the ISO 4217 currency code for the Comorian franc, the official monetary unit of the Comoros.
  • D. KMSKA
    KMSKA is the Royal Museum of Fine Arts in Antwerp, renowned for its extensive collection of Flemish and Belgian art spanning several centuries.
  • E. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbd489c819098233a111442762e completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ac939bc819081629b9eef20c4e7 completed May 2, 2026, 4:48 p.m.
NEDg Description generation batch_69f62c7b28588190839c35c19856d16f completed May 2, 2026, 4:55 p.m.
NED2 Entity disambiguation (via description) batch_69f62e403a308190a2bba3fefc420932 completed May 2, 2026, 5:02 p.m.
Created at: April 8, 2026, 9:54 p.m.