Triple

T2431855
Position Surface form Disambiguated ID Type / Status
Subject Nowshera E52863 entity
Predicate nearbyCity P350 FINISHED
Object Charsadda E54837 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: Charsadda | Statement: [Nowshera, nearbyCity, Charsadda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charsadda
Context triple: [Nowshera, nearbyCity, Charsadda]
  • A. Charsadda chosen
    Charsadda is a historic city in northwestern Pakistan known for its ancient Gandharan heritage and agricultural significance.
  • B. Tachelhit
    Tachelhit is a Berber (Amazigh) language spoken primarily in southwestern Morocco, especially in the Souss region and the High Atlas mountains.
  • C. Tarhuna
    Tarhuna is a town in northwestern Libya, southeast of Tripoli, known for its strategic role and tribal influence during the Libyan civil conflicts.
  • D. Madayya
    Madayya was a poet who served in the royal court of the Vijayanagara emperor Sri Krishnadevaraya.
  • E. Kalbeliya
    Kalbeliya is a vibrant folk dance form of the Kalbeliya (snake-charmer) community, characterized by fast, swirling movements and colorful costumes, and is recognized by UNESCO as an Intangible Cultural Heritage of Humanity.
  • 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9c915e881908d97ae4ccc83ab53 completed March 7, 2026, 6:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf68d6a481909acd43eb31660f0e completed March 9, 2026, 12:39 p.m.
Created at: March 6, 2026, 9:43 p.m.