Triple

T21146796
Position Surface form Disambiguated ID Type / Status
Subject Hedieh Tehrani E521076 entity
Predicate residence P75 FINISHED
Object Tehran, Iran 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, Iran | Statement: [Hedieh Tehrani, residence, Tehran, Iran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tehran, Iran
Context triple: [Hedieh Tehrani, residence, Tehran, Iran]
  • A. Tehran chosen
    Tehran is the capital and largest city of Iran, serving as the country's political, economic, and cultural center.
  • B. 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.
  • C. 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.
  • D. Tehrani
    Tehrani is a Persian surname most notably associated with Iranian actress Hedieh Tehrani.
  • E. Persepolis Tehran
    Persepolis Tehran is a prominent Iranian professional football club based in Tehran and one of the most successful and popular teams in Asian football.
  • 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_69e0b50c6a848190a4e525a77a319b8a completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e723fdc25481909d6648e09b069c41 completed April 21, 2026, 7:15 a.m.
Created at: April 16, 2026, 2:58 p.m.