Triple

T8047181
Position Surface form Disambiguated ID Type / Status
Subject North Kargar Campus E187582 entity
Predicate locatedIn P40 FINISHED
Object Tehran E5216 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: Tehran | Statement: [North Kargar Campus, locatedIn, Tehran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tehran
Context triple: [North Kargar Campus, locatedIn, 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 (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_69ca82b15e948190a62fd7af5218426a completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f4f0bf88190b8a706186118c977 completed March 31, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc93c407cc81908029bfdd5a0393f1 completed April 1, 2026, 3:40 a.m.
Created at: March 30, 2026, 5:24 p.m.