Triple

T1392829
Position Surface form Disambiguated ID Type / Status
Subject Zhob E30598 entity
Predicate partOf P40 FINISHED
Object Zhob Division E30598 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: Zhob Division | Statement: [Zhob, partOf, Zhob Division]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhob Division
Context triple: [Zhob, partOf, Zhob Division]
  • A. Mardan Division
    Mardan Division is an administrative division in Pakistan known for encompassing the city of Mardan and surrounding districts within the Khyber Pakhtunkhwa province.
  • B. Zhob chosen
    Zhob is a town and district in northwestern Balochistan, Pakistan, known historically as a strategic frontier outpost and regional trade center near the Afghan border.
  • C. Ghor Province
    Ghor Province is a mountainous, centrally located region of Afghanistan known for its remote terrain, historical significance, and ethnically diverse population.
  • D. Qakh District
    Qakh District is an administrative region in northwestern Azerbaijan known for its ethnically diverse population and location along the border with Georgia.
  • E. Badaro district
    Badaro district is a vibrant residential and commercial neighborhood in Beirut, Lebanon, known for its cafés, nightlife, and proximity to major cultural and governmental institutions.
  • 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_69a498fd4e408190bd73eca30ea9754c completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c360a7f08190ab7e903764b06fdf completed March 1, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace56e32608190a03485d7cb5941a8 completed March 8, 2026, 2:56 a.m.
Created at: March 1, 2026, 7:59 p.m.