Triple

T4934890
Position Surface form Disambiguated ID Type / Status
Subject Peugeot 2008 E110787 entity
Predicate assemblyLocation P40 FINISHED
Object Tehran, Iran 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, Iran | Statement: [Peugeot 2008, assemblyLocation, Tehran, Iran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tehran, Iran
Context triple: [Peugeot 2008, assemblyLocation, 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. 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.
  • 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_69bd4415eee08190bdce70276e56a5b4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7066ed548190a76a9559f90e3869 completed March 20, 2026, 4:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77b74c748190a995a26f45b79ee9 completed March 21, 2026, 10:49 a.m.
Created at: March 20, 2026, 1:30 p.m.