Triple

T11268686
Position Surface form Disambiguated ID Type / Status
Subject Shogran E266753 entity
Predicate hasNearbyPlace P3449 FINISHED
Object Naran E56154 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: Naran | Statement: [Shogran, hasNearbyPlace, Naran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naran
Context triple: [Shogran, hasNearbyPlace, Naran]
  • A. Naran chosen
    Naran is a popular mountain resort town and tourist destination in northern Pakistan, known for its scenic valleys, rivers, and access to sites like Lake Saif-ul-Malook.
  • B. Naranjal
    Naranjal is a town and canton in southwestern Ecuador known for its agricultural production and location within Guayas Province.
  • C. Banna
    Banna is the Latin name of Birdoswald Roman Fort, a key military site along Hadrian’s Wall in Roman Britain.
  • D. Tuspa
    Tuspa is an alternative name for Tushpa, the ancient capital city of the Urartian kingdom located near modern-day Lake Van in eastern Turkey.
  • E. Cerezo
    Cerezo is a Spanish surname most notably associated with Enrique Cerezo, a prominent film producer and president of Atlético Madrid.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e94f60d48190bc925c3cb88641a8 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ccd52c20819093e03bba2fd359b7 completed April 19, 2026, 12:38 p.m.
Created at: April 8, 2026, 9:31 p.m.