Triple

T9475985
Position Surface form Disambiguated ID Type / Status
Subject Beştepe Millet Camii E228518 entity
Predicate locatedIn P40 FINISHED
Object Beştepe E235355 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: Beştepe | Statement: [Beştepe Millet Camii, locatedIn, Beştepe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beştepe
Context triple: [Beştepe Millet Camii, locatedIn, Beştepe]
  • A. Beştepe chosen
    Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
  • B. Nişantaşı
    Nişantaşı is an upscale neighborhood in Istanbul known for its luxury shopping streets, stylish cafes, and elegant residential buildings.
  • C. Bağçasaray
    Bağçasaray is the Crimean Tatar name for Bakhchisaray, a historic town in Crimea that once served as the capital of the Crimean Khanate.
  • D. Kartepe
    Kartepe is a district and popular winter sports and nature tourism destination located in Turkey’s Kocaeli Province, near the Marmara region.
  • E. Kasımpaşa
    Kasımpaşa is a historic waterfront neighborhood in Istanbul, Turkey, known for its maritime heritage, working-class character, and proximity to the Golden Horn.
  • 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_69ca847162c48190b079076c9595513c completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7ff39f48819087e696c2c1ffe638 completed April 1, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69d122dbd4948190af434d1e0a281f35 completed April 4, 2026, 2:40 p.m.
Created at: March 30, 2026, 7:54 p.m.