Triple

T11310874
Position Surface form Disambiguated ID Type / Status
Subject siSwati E267830 entity
Predicate hasDialects P4251 FINISHED
Object Standard Swati E131416 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: Standard Swati | Statement: [siSwati, hasDialects, Standard Swati]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Standard Swati
Context triple: [siSwati, hasDialects, Standard Swati]
  • A. siSwati
    siSwati is a Bantu language of the Nguni group spoken primarily by the Swazi people in Eswatini and parts of South Africa.
  • B. Swati language chosen
    Swati language is a Bantu language of the Nguni group spoken primarily in Eswatini and parts of South Africa.
  • C. Awadhi
    Awadhi is an Indo-Aryan language of northern India, traditionally spoken in parts of Uttar Pradesh and surrounding regions and known for its rich literary and folk traditions.
  • D. Sant Bhasha
    Sant Bhasha is a historical North Indian devotional literary language used in Sikh and related spiritual poetry, written in the Gurmukhi script.
  • E. Kurukh
    Kurukh is an indigenous Dravidian language spoken primarily by the Oraon tribal communities in eastern and central India.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e50a7fc06881909afe85a600d25ff2 completed April 19, 2026, 5:01 p.m.
Created at: April 8, 2026, 9:32 p.m.