Triple

T17992922
Position Surface form Disambiguated ID Type / Status
Subject Municipal Committee Jhang E430421 entity
Predicate administers P123 FINISHED
Object city of Jhang NE NERFINISHED

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: city of Jhang | Statement: [Municipal Committee Jhang, administers, city of Jhang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Jhang
Context triple: [Municipal Committee Jhang, administers, city of Jhang]
  • A. Jhang chosen
    Jhang is a historic city in the Punjab province of Pakistan, known for its cultural heritage and as the birthplace of several notable figures.
  • B. 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.
  • C. Gujranwala
    Gujranwala is a major industrial city in Pakistan’s Punjab province, known for its manufacturing base and historical significance in the region.
  • D. Mandi Bahauddin
    Mandi Bahauddin is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub in the region.
  • E. Bahawalnagar
    Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b2a0f8588190b6090c7cce60a35f completed April 19, 2026, 10:46 a.m.
Created at: April 10, 2026, 10:23 a.m.