Triple

T15714537
Position Surface form Disambiguated ID Type / Status
Subject Larkana Campus E380927 entity
Predicate locatedIn P40 FINISHED
Object Larkana E77818 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: Larkana | Statement: [Larkana Campus, locatedIn, Larkana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larkana
Context triple: [Larkana Campus, locatedIn, Larkana]
  • A. Larkana chosen
    Larkana is a major city in Pakistan known for its historical significance, including proximity to the ancient Indus Valley site of Mohenjo-daro and its association with the Bhutto political family.
  • B. Shakardara
    Shakardara is a town and administrative settlement in Pakistan’s Khyber Pakhtunkhwa province, known for its role within the Kohat region.
  • C. Khar
    Khar is a suburban neighborhood in Mumbai, India, known for its residential areas, shopping streets, and proximity to the Arabian Sea.
  • D. Khar
    Khar is a town in northwestern Pakistan that serves as the administrative and commercial center of the Bajaur region in Khyber Pakhtunkhwa.
  • E. Tarkarli
    Tarkarli is a coastal village in Maharashtra, India, known for its pristine beaches, clear waters, and popular scuba diving and snorkeling spots.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f90aea0819082a9e9fe0f7780b0 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff7581302c8190918266f04bcf2231 completed May 9, 2026, 5:57 p.m.
Created at: April 10, 2026, 4:45 a.m.