Triple

T4139078
Position Surface form Disambiguated ID Type / Status
Subject Hazara E89227 entity
Predicate hasDistrict P459 FINISHED
Object Torghar District E274661 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: Torghar District | Statement: [Hazara, hasDistrict, Torghar District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Torghar District
Context triple: [Hazara, hasDistrict, Torghar District]
  • A. Torghar District chosen
    Torghar District is a small, mountainous administrative district in Pakistan’s Khyber Pakhtunkhwa province, known for its tribal communities and rugged terrain.
  • B. Rusafa District
    Rusafa District is a central administrative area of Baghdad, Iraq, known for encompassing key cultural and historical landmarks, including major monuments and public institutions.
  • C. Siha District
    Siha District is an administrative district in northern Tanzania, located within the Kilimanjaro Region near the slopes of Mount Kilimanjaro.
  • D. Shabran District
    Shabran District is an administrative region in northeastern Azerbaijan known for its historical sites and location near the Caspian Sea.
  • E. Pishin District
    Pishin District is an administrative district in the Balochistan province of Pakistan, known for its agricultural economy and predominantly Pashtun population.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02485a788190ba6ee769e663b2d3 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f2e787881908a9721877b0fd4ae completed March 14, 2026, 3:30 p.m.
Created at: March 9, 2026, 3:43 p.m.