Triple

T21685590
Position Surface form Disambiguated ID Type / Status
Subject Divan of Sana'i E535220 entity
Predicate originalRegion P410 FINISHED
Object Ghazna NE NERFINISHED

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: Ghazna | Statement: [Divan of Sana'i, originalRegion, Ghazna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ghazna
Context triple: [Divan of Sana'i, originalRegion, Ghazna]
  • A. Ghazni chosen
    Ghazni is a historic city in central Afghanistan that has long held strategic and military importance, including as a key battleground during the Anglo-Afghan conflicts.
  • B. Mahmudabad
    Mahmudabad is a town and municipal body in the Sitapur district of Uttar Pradesh, India, known for its local markets and administrative significance in the region.
  • C. Mahmudabad
    Mahmudabad is a coastal city in northern Iran, situated along the Caspian Sea in Mazandaran Province and known for its beaches and tourism.
  • D. Homayunshahr
    Homayunshahr is a city in Iran best known as the birthplace of acclaimed filmmaker Asghar Farhadi.
  • E. Balkh
    Balkh is an ancient city in northern Afghanistan, historically a major center of Persian culture, trade, and Islamic scholarship.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c469b6ec8190aee4cadd1527db91 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef96ca668481909f53853c7a8ea811 completed April 27, 2026, 5:03 p.m.
Created at: April 16, 2026, 6:44 p.m.