Triple

T1296355
Position Surface form Disambiguated ID Type / Status
Subject Ibn Arabi E27660 entity
Predicate travelledTo P21947 FINISHED
Object Konya E14759 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: Konya | Statement: [Ibn Arabi, travelledTo, Konya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Konya
Context triple: [Ibn Arabi, travelledTo, Konya]
  • A. Konya chosen
    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.
  • B. Kayseri
    Kayseri is a historic city in central Turkey, known for its Seljuk and Ottoman architectural heritage and its role as a major commercial and cultural center in Anatolia.
  • C. 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.
  • D. Gaziantep
    Gaziantep is a major city in southeastern Turkey known for its rich history, cultural heritage, and renowned pistachio-based cuisine, especially baklava.
  • E. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • 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_69a496d6682881909ba658f1c1e0e2b0 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c48bec548190b25d4a74b323cc1b completed March 1, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad796ef934819083713b715b93c1b4 completed March 8, 2026, 1:28 p.m.
Created at: March 1, 2026, 7:51 p.m.