Triple

T20764443
Position Surface form Disambiguated ID Type / Status
Subject Liaquat University of Medical and Health Sciences E511057 entity
Predicate locatedIn P40 FINISHED
Object Jamshoro 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: Jamshoro | Statement: [Liaquat University of Medical and Health Sciences, locatedIn, Jamshoro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jamshoro
Context triple: [Liaquat University of Medical and Health Sciences, locatedIn, Jamshoro]
  • A. Jamshoro chosen
    Jamshoro is a city in the Sindh province of Pakistan known as an important educational hub, hosting several major universities and research institutions.
  • B. Jauharabad
    Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
  • C. Wazirabad
    Wazirabad is a city in the Gujranwala District of Punjab, Pakistan, known for its cutlery industry and strategic location near the Chenab River.
  • D. Hafizabad
    Hafizabad is a prominent city in Pakistan’s Punjab province, known for its rice production and role as an agricultural and commercial center.
  • E. Shujabad
    Shujabad is a city in southern Punjab, Pakistan, known for its agricultural economy and proximity to the regional center of Multan.
  • 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_69e0b4ca01148190ac018e57e0cab46f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c24b18b8819082e61104be6f83a3 completed April 21, 2026, 12:18 a.m.
Created at: April 16, 2026, 12:36 p.m.