Triple

T21307353
Position Surface form Disambiguated ID Type / Status
Subject Hossein Fatemi E525233 entity
Predicate workLocation P7 FINISHED
Object Isfahan 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: Isfahan | Statement: [Hossein Fatemi, workLocation, Isfahan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isfahan
Context triple: [Hossein Fatemi, workLocation, Isfahan]
  • A. Isfahan chosen
    Isfahan is a historic Iranian city renowned for its Safavid-era architecture, grand mosques, and role as a major political and cultural center in early modern Persia.
  • B. Mashhad
    Mashhad is a major city in northeastern Iran renowned as a leading religious and cultural center of the Islamic world, centered around the shrine of Imam Reza.
  • C. شیراز
    شیراز یکی از مهم‌ترین و تاریخی‌ترین شهرهای ایران است که به‌عنوان مرکز فرهنگ، ادب و شعر فارسی شناخته می‌شود.
  • D. Kashan
    Kashan is an Iranian city renowned for its rich history, traditional architecture, and production of high-quality Persian carpets.
  • E. Hamadan
    Hamadan is an ancient city in western Iran, historically significant as a major center of Persian Jewish life and one of the oldest continuously inhabited cities in the region.
  • 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_69e0b518b8948190ad69cf9a8784d397 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e75aa69b40819081e74c042e7cd105 completed April 21, 2026, 11:08 a.m.
Created at: April 16, 2026, 4:05 p.m.