Triple

T6486203
Position Surface form Disambiguated ID Type / Status
Subject Punjab, Pakistan E146516 entity
Predicate containsCity P294 FINISHED
Object Faisalabad E475732 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: Faisalabad | Statement: [Punjab, Pakistan, containsCity, Faisalabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faisalabad
Context triple: [Punjab, Pakistan, containsCity, Faisalabad]
  • A. Faisalabad chosen
    Faisalabad is a major industrial city in Pakistan’s Punjab province, known especially for its large textile industry and role as a commercial hub.
  • B. Bahawalpur
    Bahawalpur is a historic city in southern Punjab, Pakistan, known for its former princely state status, grand palaces, and proximity to the Cholistan Desert.
  • 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. Sukkur
    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.
  • 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_69c0090158c08190af0df9a2348d2d52 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a706d4c8190b7a3cc8855abcecb completed March 22, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c674074df08190a32f7014b2df0120 completed March 27, 2026, 12:11 p.m.
Created at: March 22, 2026, 4:52 p.m.