Triple

T6713207
Position Surface form Disambiguated ID Type / Status
Subject Chartres E153197 entity
Predicate twinnedWith P1072 FINISHED
Object Ivano-Frankivsk E156600 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: Ivano-Frankivsk | Statement: [Chartres, twinnedWith, Ivano-Frankivsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ivano-Frankivsk
Context triple: [Chartres, twinnedWith, Ivano-Frankivsk]
  • A. Ivano-Frankivsk chosen
    Ivano-Frankivsk is a historic city in western Ukraine known as a cultural, economic, and administrative center of the Carpathian region.
  • B. Ternopil
    Ternopil is a city in western Ukraine known as a regional cultural and economic center with a historic old town and a picturesque lakeside setting.
  • C. Khmelnytskyi
    Khmelnytskyi is a regional city in western Ukraine known as an important administrative, economic, and cultural center.
  • D. Vinnytsia
    Vinnytsia is a major city in central Ukraine known as an important administrative, economic, and cultural center on the Southern Bug River.
  • E. Kropyvnytskyi
    Kropyvnytskyi is a regional city in central Ukraine known as an important administrative, cultural, and transportation center.
  • 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d121a92c8190a03f384a8aba84da completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c700948788819087f9b466be337286 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:07 p.m.