Triple

T9055188
Position Surface form Disambiguated ID Type / Status
Subject Tat people E216978 entity
Predicate region P40 FINISHED
Object Khizi District E153533 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: Khizi District | Statement: [Tat people, region, Khizi District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khizi District
Context triple: [Tat people, region, Khizi District]
  • A. Ziarat District
    Ziarat District is a mountainous administrative region in northeastern Balochistan, Pakistan, known for its juniper forests and the historic Ziarat Residency.
  • B. Tabasaran District
    Tabasaran District is an administrative district in the Republic of Dagestan, Russia, known for its predominantly Tabasaran-speaking population and mountainous rural landscape.
  • C. Nasirabad District
    Nasirabad District is an administrative district in the Balochistan province of Pakistan, known for its agricultural economy and strategic location in the province’s eastern plains.
  • D. Hesarak District
    Hesarak District is an administrative district located in eastern Afghanistan within Nangarhar Province.
  • E. Qakh District chosen
    Qakh District is an administrative region in northwestern Azerbaijan known for its ethnically diverse population and location along the border with Georgia.
  • 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_69ca83d4425481909a319dab847724ec completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc7a7488188190b3dd6bc2f2377503 completed April 1, 2026, 1:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69d02fd2a1e88190bc8d8c2b634399dd completed April 3, 2026, 9:23 p.m.
Created at: March 30, 2026, 7:10 p.m.