Triple

T3668401
Position Surface form Disambiguated ID Type / Status
Subject Sukkur E77817 entity
Predicate locatedNear P294 FINISHED
Object Khairpur E160202 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: Khairpur | Statement: [Sukkur, locatedNear, Khairpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khairpur
Context triple: [Sukkur, locatedNear, Khairpur]
  • A. Khairpur chosen
    Khairpur is a historic city in Sindh, Pakistan, known for its former princely state status under the Talpur rulers and its rich cultural and architectural heritage.
  • 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. Shikarpur
    Shikarpur is a historic city in the Sindh province of Pakistan, known for its old trading heritage and distinctive cultural and architectural traditions.
  • D. Sialkot
    Sialkot is a major industrial city in Pakistan’s Punjab province, renowned globally for its production of sports goods and surgical instruments.
  • E. Chakwal
    Chakwal is a city in Pakistan’s Punjab province, known as a regional administrative and commercial center in the Potohar Plateau area.
  • 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_69ad85e083008190b2e1b7085fe500bd completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc42997d88190bc765559bd7645fc completed March 8, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c688e0c8190a7e9ea3fe010c361 completed March 14, 2026, 8:29 a.m.
Created at: March 8, 2026, 3:25 p.m.