Triple

T2495155
Position Surface form Disambiguated ID Type / Status
Subject Khyber Pakhtunkhwa E52137 entity
Predicate hasAbbreviation P43 FINISHED
Object KP E52137 NE FINISHED

How this triple was built (2 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: KP | Statement: [Khyber Pakhtunkhwa, hasAbbreviation, KP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KP
Context triple: [Khyber Pakhtunkhwa, hasAbbreviation, KP]
  • A. KP chosen
    KP is the commonly used abbreviation for Khyber Pakhtunkhwa, a province in northwestern Pakistan known for its mountainous terrain and diverse ethnic communities.
  • B. PK
    PK is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Pakistan in international standards and systems.
  • C. KC
    KC is a common shorthand nickname for Kansas City, Missouri, a major Midwestern U.S. city known for its jazz heritage, barbecue, and sports teams.
  • D. KC
    KC is the vehicle registration code used on license plates for the district of Kronach in Upper Franconia, Germany.
  • E. KE
    KE is the IATA airline designator for Korean Air, the flag carrier and largest airline of South Korea.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ab4955111c8190835bf619adec21ff completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd19541048190b9e39db119c20fe8 completed March 7, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b8789c88190b0300af1260eb9bd completed March 9, 2026, 8:20 p.m.
Created at: March 6, 2026, 9:45 p.m.