Triple

T13250232
Position Surface form Disambiguated ID Type / Status
Subject Beypazarı E315505 entity
Predicate hasProduct P3585 FINISHED
Object Beypazarı mineral water E315505 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: Beypazarı mineral water | Statement: [Beypazarı, hasProduct, Beypazarı mineral water]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beypazarı mineral water
Context triple: [Beypazarı, hasProduct, Beypazarı mineral water]
  • A. Beyşehir
    Beyşehir is a town and district in central Turkey known for its large freshwater lake, Lake Beyşehir, and its rich Seljuk-era architectural heritage.
  • B. Beypazarı chosen
    Beypazarı is a historic district and town in central Turkey known for its well-preserved Ottoman-era houses, traditional markets, and mineral water.
  • C. Salıpazarı
    Salıpazarı is a town and district in northern Turkey known for its rural character and location within Samsun Province along the Black Sea region.
  • D. Keban
    Keban is a town in eastern Turkey located near the Euphrates River, known primarily for its proximity to the large hydroelectric Keban Dam.
  • E. Gölbaşı
    Gölbaşı is a district and suburban area of Ankara in central Turkey, known for its lakes, recreational areas, and proximity to the capital city.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f71c5388190a6e122e14384efd7 completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff393898819083bdf726466fcbe0 completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:24 p.m.