Triple

T8597817
Position Surface form Disambiguated ID Type / Status
Subject Beykoz E203594 entity
Predicate contains P35 FINISHED
Object Paşabahçe E191350 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: Paşabahçe | Statement: [Beykoz, contains, Paşabahçe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paşabahçe
Context triple: [Beykoz, contains, Paşabahçe]
  • A. Papazın Çayırı
    Papazın Çayırı was the historic football ground in Istanbul that served as an early home venue for major Turkish clubs before being replaced by the modern Şükrü Saracoğlu Stadium.
  • B. Bostan
    Bostan is a town in Pakistan’s Balochistan province that serves as a regional railway junction and transit point between Quetta and Chaman.
  • C. Murzuq
    Murzuq is an oasis town in southwestern Libya that historically served as an important Saharan trade and caravan center in the Fezzan region.
  • D. Garipçe chosen
    Garipçe is a small coastal village on the European side of Istanbul, Turkey, situated at the entrance of the Bosphorus Strait.
  • E. Çalıkuşu
    Çalıkuşu is a classic early 20th-century Turkish novel that follows the life and struggles of an idealistic young female teacher, and is widely regarded as one of the foundational works of modern Turkish literature.
  • 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46cacbe88190b95beeedc9f480b0 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8dd86d08190a7f8e674e16dd8b6 completed April 2, 2026, 5:35 p.m.
Created at: March 30, 2026, 6:24 p.m.