Triple

T16447702
Position Surface form Disambiguated ID Type / Status
Subject Multan Fort E399473 entity
Predicate hasView P854 FINISHED
Object Multan city E90805 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: Multan city | Statement: [Multan Fort, hasView, Multan city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Multan city
Context triple: [Multan Fort, hasView, Multan city]
  • A. Multan chosen
    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.
  • 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. Bahawalnagar
    Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
  • D. Multan District
    Multan District is an administrative district in Punjab, Pakistan, centered on the historic city of Multan and known for its cultural, economic, and religious significance in the region.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32cddfc3c8190919b49f74b7e8e1a completed April 18, 2026, 7:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0084aa47408190abe2ffaab84cdd85 completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:10 a.m.