Triple

T19467902
Position Surface form Disambiguated ID Type / Status
Subject Uluka E487046 entity
Predicate hasISO6392Code P189 FINISHED
Object kan
kan is the ISO 639-2 code for the Kannada language, a major Dravidian language spoken predominantly in the Indian state of Karnataka.
 E1377188 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: kan | Statement: [Uluka, hasISO6392Code, kan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: kan
Context triple: [Uluka, hasISO6392Code, kan]
  • A. kan
    Kan is a Mayan term meaning “snake” or “serpent,” often associated with divinity, power, and the feathered serpent deity in Mesoamerican cultures.
  • B. KAN
    KAN is the IATA airport code for Mallam Aminu Kano International Airport, a major airport serving Kano in northern Nigeria.
  • C. Ka
    Ka is an American underground rapper and producer from Brownsville, Brooklyn, known for his minimalist, introspective style and dense, poetic lyricism.
  • D. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • E. Ka
    Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
  • 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: kan
Triple: [Uluka, hasISO6392Code, kan]
Generated description
kan is the ISO 639-2 code for the Kannada language, a major Dravidian language spoken predominantly in the Indian state of Karnataka.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: kan
Target entity description: kan is the ISO 639-2 code for the Kannada language, a major Dravidian language spoken predominantly in the Indian state of Karnataka.
  • A. kan
    Kan is a Mayan term meaning “snake” or “serpent,” often associated with divinity, power, and the feathered serpent deity in Mesoamerican cultures.
  • B. KAN
    KAN is the IATA airport code for Mallam Aminu Kano International Airport, a major airport serving Kano in northern Nigeria.
  • C. Ka
    Ka is an American underground rapper and producer from Brownsville, Brooklyn, known for his minimalist, introspective style and dense, poetic lyricism.
  • D. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • E. Ka
    Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
  • 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633e4b230819097c8804ee91988ea completed April 20, 2026, 2:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a073b40271c8190a27b00e6533ed1a0 completed May 15, 2026, 3:26 p.m.
NEDg Description generation batch_6a073c19c3b88190a6114d272ebd5fbc completed May 15, 2026, 3:30 p.m.
NED2 Entity disambiguation (via description) batch_6a073d25ba448190a62777b68d2f3136 completed May 15, 2026, 3:35 p.m.
Created at: April 10, 2026, 1:39 p.m.