Triple

T7796672
Position Surface form Disambiguated ID Type / Status
Subject Shangla District E180315 entity
Predicate containsSettlement P847 FINISHED
Object Kana
Kana is a settlement located within Pakistan’s Shangla District in the Khyber Pakhtunkhwa province.
 E694082 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: Kana | Statement: [Shangla District, containsSettlement, Kana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kana
Context triple: [Shangla District, containsSettlement, Kana]
  • A. Kana
    Kana is the Japanese syllabic writing system comprising hiragana and katakana, used to represent native words, grammatical elements, and foreign terms.
  • B. Katakana
    Katakana is one of the two main Japanese phonetic writing systems, primarily used for foreign words, onomatopoeia, emphasis, and technical or scientific terms.
  • C. Kanji
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • D. Hiragana
    Hiragana is a Japanese phonetic syllabary used primarily for native words, grammatical elements, and beginners’ reading and writing.
  • E. Kikakui script
    The Kikakui script is an indigenous syllabary developed in the 19th century for writing the Mende language of Sierra Leone.
  • 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: Kana
Triple: [Shangla District, containsSettlement, Kana]
Generated description
Kana is a settlement located within Pakistan’s Shangla District in the Khyber Pakhtunkhwa province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kana
Target entity description: Kana is a settlement located within Pakistan’s Shangla District in the Khyber Pakhtunkhwa province.
  • A. Kana
    Kana is the Japanese syllabic writing system comprising hiragana and katakana, used to represent native words, grammatical elements, and foreign terms.
  • B. Katakana
    Katakana is one of the two main Japanese phonetic writing systems, primarily used for foreign words, onomatopoeia, emphasis, and technical or scientific terms.
  • C. Kanji
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • D. Hiragana
    Hiragana is a Japanese phonetic syllabary used primarily for native words, grammatical elements, and beginners’ reading and writing.
  • E. Kikakui script
    The Kikakui script is an indigenous syllabary developed in the 19th century for writing the Mende language of Sierra Leone.
  • 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_69ca827d22208190b4dc5aa680edcf5d completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae982c3b48190a35afe655fb20d55 completed March 30, 2026, 9:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb13f866ac8190bca2b8477b62d7e4 completed March 31, 2026, 12:23 a.m.
NEDg Description generation batch_69cb1730900c8190bc0322c4b6a3772f completed March 31, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_69cb1a3e6da08190bf4f82b59db41333 completed March 31, 2026, 12:50 a.m.
Created at: March 30, 2026, 4:32 p.m.