Triple

T12741984
Position Surface form Disambiguated ID Type / Status
Subject Majha (Punjab) E304509 entity
Predicate crossedBy P416 FINISHED
Object Beas River E18137 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: Beas River | Statement: [Majha (Punjab), crossedBy, Beas River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beas River
Context triple: [Majha (Punjab), crossedBy, Beas River]
  • A. Beas River chosen
    The Beas River is a major river in northern India that flows through the state of Punjab, playing a vital role in its agriculture and ecology.
  • B. Panj River
    The Panj River is a significant Central Asian waterway that forms much of the border between Tajikistan and Afghanistan and serves as a principal headstream of the Amu Darya.
  • C. Bhera River
    The Bhera River is a significant tributary watercourse that feeds into eastern India’s Damodar River system.
  • D. Khasa River
    The Khasa River is a seasonal river in northern Iraq that flows through the city of Kirkuk and serves as one of its main waterways.
  • E. Panjkora River
    The Panjkora River is a scenic mountain river in Pakistan’s Khyber Pakhtunkhwa province, known for flowing through the lush, forested landscapes of Kumrat Valley and supporting local agriculture and tourism.
  • 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96bd321bc81908eb61cc05b550754 completed April 10, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af49d2c4819097168712af7d4c15 completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:26 p.m.