Triple

T1105508
Position Surface form Disambiguated ID Type / Status
Subject Argo E25479 entity
Predicate setInCity P7747 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: [Argo, setInCity, Tehran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tehran
Context triple: [Argo, setInCity, Tehran]
  • A. Tehran chosen
    Tehran is the capital and largest city of Iran, serving as the country's political, economic, and cultural center.
  • B. 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.
  • C. 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.
  • D. Tabriz
    Tabriz is a historic city in northwestern Iran that has long served as a major political, commercial, and cultural center in the region.
  • 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 (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_69a49428d4448190b3b36991ceae87ce completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b9e21f048190bf4b63dd2c7c7641 completed March 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8309594c8190986b048b8982f153 completed March 7, 2026, 7:56 p.m.
Created at: March 1, 2026, 7:43 p.m.