Triple

T18908432
Position Surface form Disambiguated ID Type / Status
Subject Jaroměř railway station E462529 entity
Predicate locatedIn P40 FINISHED
Object Jaroměř NE NERFINISHED

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: Jaroměř | Statement: [Jaroměř railway station, locatedIn, Jaroměř]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jaroměř
Context triple: [Jaroměř railway station, locatedIn, Jaroměř]
  • A. Jaroměř chosen
    Jaroměř is a historic town in the northeastern Czech Republic known for its preserved architecture and proximity to the confluence of the Elbe and Metuje rivers.
  • B. Zbyhněv
    Zbyhněv is a given name, likely a variant or regional form of the Slavic name Zbigniew.
  • C. Jauru
    Jauru is an alternative name for the Yawuru, an Aboriginal Australian people traditionally associated with the Broome region of Western Australia.
  • D. Třemošná
    Třemošná is a small town in the western Czech Republic, located near the city of Plzeň in the Plzeň Region.
  • E. Jelínek
    Jelínek is a Czech surname commonly borne by individuals of Czech origin and appears in various cultural, academic, and professional contexts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dcfd05bc819088903cca13cc2846 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c52eed1881908929dace845ae008 completed April 20, 2026, 6:18 a.m.
Created at: April 10, 2026, 11:58 a.m.