Triple

T361711
Position Surface form Disambiguated ID Type / Status
Subject Recep Tayyip Erdoğan E7868 entity
Predicate workLocation P7 FINISHED
Object Ankara E11226 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: Ankara | Statement: [Recep Tayyip Erdoğan, workLocation, Ankara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ankara
Context triple: [Recep Tayyip Erdoğan, workLocation, Ankara]
  • A. Ankara chosen
    Ankara is the political and administrative center of Turkey, known for hosting the country’s government institutions and foreign embassies.
  • B. Istanbul
    Istanbul is a transcontinental metropolis straddling Europe and Asia, renowned as Turkey’s cultural and economic hub and for its rich history as the former capital of the Byzantine and Ottoman Empires.
  • C. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • D. Bursa
    Bursa is a major city in northwestern Turkey known historically as the first capital of the Ottoman Empire and today as an important industrial and cultural center.
  • E. Konya
    Konya is a major city in central Anatolia known for its rich Seljuk heritage and as the home of the Sufi mystic Rumi and the Whirling Dervishes.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebce64c88190a0a8edcc7095f78b completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3eca750748190b5a2914f318bc1c2 completed March 1, 2026, 7:37 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.