Triple

T11419160
Position Surface form Disambiguated ID Type / Status
Subject Kadıköy Pier E270571 entity
Predicate near P350 FINISHED
Object Moda neighborhood E277135 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: Moda neighborhood | Statement: [Kadıköy Pier, near, Moda neighborhood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moda neighborhood
Context triple: [Kadıköy Pier, near, Moda neighborhood]
  • A. Moda neighborhood chosen
    Moda neighborhood is a historic, seaside district in Istanbul’s Asian-side borough of Kadıköy, known for its tree-lined streets, cafes, and vibrant cultural scene.
  • B. Roda neighborhood
    Roda neighborhood is a residential and cultural district located on Roda Island in Cairo, Egypt, known for its historic sites and Nile-side setting.
  • C. Kalorama neighborhood
    Kalorama neighborhood is an affluent, historic residential area in Northwest Washington, D.C., known for its embassies, stately homes, and prominent political residents.
  • D. Palacio neighborhood
    Palacio neighborhood is a historic central area of Madrid known for landmarks like the Royal Palace and Almudena Cathedral.
  • E. Adelfas neighborhood
    Adelfas neighborhood is a residential district within Madrid’s Retiro area, known for its quiet streets and proximity to major transport links and green spaces.
  • 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_69d6aaddeaa8819088b30ef7b50598c9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d801b20ce08190befc98379b879985 completed April 9, 2026, 7:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b88f80d88190b91b63d0b7457c25 completed April 20, 2026, 5:24 a.m.
Created at: April 8, 2026, 9:34 p.m.