Triple

T7857312
Position Surface form Disambiguated ID Type / Status
Subject National Accountability Bureau E182409 entity
Predicate hasOffice P1268 FINISHED
Object Sukkur E77817 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: Sukkur | Statement: [National Accountability Bureau, hasOffice, Sukkur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sukkur
Context triple: [National Accountability Bureau, hasOffice, Sukkur]
  • A. Sukkur chosen
    Sukkur is a major city in Pakistan known for its strategic location on the Indus River and its role as an important commercial and cultural center in northern Sindh.
  • B. Faisalabad
    Faisalabad is a major industrial city in Pakistan’s Punjab province, known especially for its large textile industry and role as a commercial hub.
  • C. Multan
    Multan is a historic city in southern Punjab, Pakistan, renowned as a major cultural, commercial, and Sufi spiritual center with a legacy spanning over two millennia.
  • D. Bahawalnagar
    Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
  • E. Rahim Yar Khan
    Rahim Yar Khan is a major city in southern Punjab, Pakistan, known as an important commercial and agricultural center in the Seraiki-speaking region.
  • 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_69ca82887fd48190975896bf38c4596b completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb1a76f8648190976b488d0d8658ef completed March 31, 2026, 12:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05422b25c819098189ac202c20123 completed April 3, 2026, 11:58 p.m.
Created at: March 30, 2026, 4:52 p.m.