Triple

T14266061
Position Surface form Disambiguated ID Type / Status
Subject Wedding district E353646 entity
Predicate borderedBy P224 FINISHED
Object Mitte district E353420 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: Mitte district | Statement: [Wedding district, borderedBy, Mitte district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitte district
Context triple: [Wedding district, borderedBy, Mitte district]
  • A. Mitte district chosen
    Mitte district is a central borough of Berlin known for its historic landmarks, government buildings, and cultural institutions.
  • B. Buyende District
    Buyende District is an administrative district in eastern Uganda, known for its rural communities and location along the shores of Lake Kyoga.
  • C. Parchim district
    Parchim district was a former administrative district in the state of Mecklenburg-Vorpommern in northern Germany, characterized by its rural landscape, small towns, and numerous rivers and lakes.
  • D. Meilen District
    Meilen District is an administrative district in the canton of Zürich, Switzerland, located along the northeastern shore of Lake Zurich and encompassing several affluent suburban municipalities.
  • E. Weidu District
    Weidu District is an urban district that serves as the central administrative area of Xuchang city in Henan Province, China.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6357a8188190ba518a486521052b completed April 14, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd326551b08190ae8fe220a6422339 completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:09 a.m.