Triple

T12659815
Position Surface form Disambiguated ID Type / Status
Subject Haro River E302387 entity
Predicate hasDam P8736 FINISHED
Object Khanpur Dam E184856 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: Khanpur Dam | Statement: [Haro River, hasDam, Khanpur Dam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khanpur Dam
Context triple: [Haro River, hasDam, Khanpur Dam]
  • A. Nangal Dam
    Nangal Dam is a hydroelectric and irrigation dam located on the Sutlej River in the Indian state of Punjab.
  • B. Rawal Dam chosen
    Rawal Dam is a water reservoir structure near Islamabad, Pakistan, built to store and supply water from Rawal Lake for the surrounding region.
  • C. Satpara Dam
    Satpara Dam is a multipurpose concrete dam in Gilgit-Baltistan, Pakistan, built to generate hydroelectric power, provide irrigation, and supply drinking water using the waters of Satpara Lake.
  • D. Bisalpur Dam
    Bisalpur Dam is a major reservoir and water supply dam in Rajasthan, India, crucial for providing drinking water and irrigation to several nearby cities and regions.
  • E. Mangla Dam
    Mangla Dam is a major multipurpose embankment dam in Pakistan, known for hydroelectric power generation, irrigation support, and being one of the largest dams in the country.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9617b07ec8190b714f04ae6654060 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f66885e44c8190a650301b0e86d0f4 completed May 2, 2026, 9:11 p.m.
Created at: April 9, 2026, 5:19 p.m.