Triple

T969428
Position Surface form Disambiguated ID Type / Status
Subject RegioExpress E20911 entity
Predicate languageVariant P5595 FINISHED
Object RegioExpress (Italian) E20911 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: RegioExpress (Italian) | Statement: [RegioExpress, languageVariant, RegioExpress (Italian)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RegioExpress (Italian)
Context triple: [RegioExpress, languageVariant, RegioExpress (Italian)]
  • A. RegioExpress chosen
    RegioExpress is a category of Swiss regional express trains that provide relatively fast, limited-stop connections between major and medium-sized towns.
  • B. InterRegio
    InterRegio is a category of medium- to long-distance passenger trains in several European countries that provides relatively fast regional connections between major cities and regions.
  • C. Thalys
    Thalys is a high-speed international train service connecting major cities in France, Belgium, the Netherlands, and Germany.
  • D. InterCity
    InterCity is a category of long-distance passenger trains in several European countries, notably providing fast, regular intercity rail services.
  • E. Ouigo
    Ouigo is a low-cost high-speed train service operated by France's SNCF, offering budget TGV travel with simplified onboard services.
  • 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_69a493b33d2c81909c52c369d3ca8436 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b4481f508190adcf0a965a23862c completed March 1, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1cd9705c8190adf1fb72188cc84e completed March 7, 2026, 12:40 p.m.
Created at: March 1, 2026, 7:40 p.m.