Triple

T36704
Position Surface form Disambiguated ID Type / Status
Subject Tehran Conference E727 entity
Predicate country P26 FINISHED
Object Iran E3491 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: Iran | Statement: [Tehran Conference, country, Iran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iran
Context triple: [Tehran Conference, country, Iran]
  • A. Iran chosen
    Iran is a Middle Eastern country that, after being occupied by British and Soviet forces in 1941, aligned with the Allies in World War II and served as a crucial supply corridor to the Soviet Union.
  • B. Iraq
    Iraq is a Middle Eastern country historically significant for its ancient Mesopotamian civilizations and its major role in 20th- and 21st-century geopolitics and conflicts.
  • C. Saudi Arabia
    Saudi Arabia is a Middle Eastern kingdom on the Arabian Peninsula known for its vast oil reserves, custodianship of Islam’s holiest sites, and significant geopolitical influence.
  • D. Pakistan
    Pakistan is a South Asian country bordering India, Afghanistan, Iran, and China, known for its diverse cultures, strategic geopolitical position, and significant agricultural and nuclear capabilities.
  • E. Israel
    Israel is a Middle Eastern country known for its significant historical and religious sites, advanced technology sector, and developed, high-income economy.
  • 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24acbb90881908c9f77e74034eb52 completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a266e34b548190a0fc4dea2cf37e52 completed Feb. 28, 2026, 3:54 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.