Triple

T15876202
Position Surface form Disambiguated ID Type / Status
Subject Forough Farrokhzad E384958 entity
Predicate deathPlace P21 FINISHED
Object Tehran 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: Tehran | Statement: [Forough Farrokhzad, deathPlace, Tehran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tehran
Context triple: [Forough Farrokhzad, deathPlace, Tehran]
  • A. Tehran chosen
    Tehran is the capital and largest city of Iran, serving as the country's political, economic, and cultural center.
  • B. Shahr-e Rey
    Shahr-e Rey is an ancient city now absorbed into the metropolitan area of Tehran, Iran, known for its long history as a major political and cultural center in the region.
  • C. Teheran-ro
    Teheran-ro is a major business and technology corridor in Seoul, South Korea, known for its concentration of corporate headquarters, startups, and high-rise office buildings.
  • D. Isfahan
    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.
  • E. 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.
  • 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e155fdc1b881909d1c82c4c66a195a completed April 16, 2026, 9:34 p.m.
Created at: April 10, 2026, 4:51 a.m.