Triple

T4159664
Position Surface form Disambiguated ID Type / Status
Subject Ирон E91499 entity
Predicate hasAlternativeName P39 FINISHED
Object Iron dialect E124251 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: Iron dialect | Statement: [Ирон, hasAlternativeName, Iron dialect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iron dialect
Context triple: [Ирон, hasAlternativeName, Iron dialect]
  • A. Scharrel dialect
    The Scharrel dialect is a local variety of Saterland Frisian spoken in and around the village of Scharrel in Lower Saxony, Germany.
  • B. Intemelian dialect
    The Intemelian dialect is a regional variety of the Ligurian language traditionally spoken around Ventimiglia and nearby coastal areas of northwestern Italy and southeastern France.
  • C. Digor dialect chosen
    The Digor dialect is a major variety of the Ossetian language spoken primarily in the western regions of North Ossetia–Alania and parts of the central Caucasus.
  • D. Limba
    The Limba are one of the largest and oldest indigenous ethnic groups in Sierra Leone, known for their distinct language, cultural traditions, and historical role in the country’s northern regions.
  • E. Westronic
    Westronic is a company known for its work in industrial and utility communication systems, including contributions to SCADA and telemetry technologies.
  • 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_69aed9626ebc8190a39de631788bea3e completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af029454d08190b7ff32776081fabc completed March 9, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f40678481908894ff315932a610 completed March 14, 2026, 3:31 p.m.
Created at: March 9, 2026, 3:44 p.m.