Triple

T2684685
Position Surface form Disambiguated ID Type / Status
Subject Kabul River E57455 entity
Predicate passesNear P416 FINISHED
Object Nowshera E52863 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: Nowshera | Statement: [Kabul River, passesNear, Nowshera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nowshera
Context triple: [Kabul River, passesNear, Nowshera]
  • A. Nowshera chosen
    Nowshera is a city in northern Pakistan known as an important commercial and military center in the Khyber Pakhtunkhwa province.
  • B. Mansehra
    Mansehra is a major city in northern Pakistan known as a gateway to the Kaghan Valley and the Karakoram Highway.
  • C. Khuldabad
    Khuldabad is a historic town in Maharashtra, India, renowned as the burial site of the Mughal emperor Aurangzeb and several prominent Sufi saints.
  • D. Parachinar
    Parachinar is a major town in northwestern Pakistan near the Afghan border, known as the administrative center of Kurram District and for its strategic and sectarian-sensitive location.
  • E. Taxila
    Taxila was an ancient city in present-day Pakistan that served as a major center of learning, trade, and administration in South Asia.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9edba5c8190b86d6cba0f1964e2 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf5b19b88190982a669501463fa9 completed March 10, 2026, 5:42 a.m.
Created at: March 6, 2026, 9:54 p.m.