Triple

T16356380
Position Surface form Disambiguated ID Type / Status
Subject Swazi language E397190 entity
Predicate alternateName P39 FINISHED
Object Swati E58238 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: Swati | Statement: [Swazi language, alternateName, Swati]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swati
Context triple: [Swazi language, alternateName, Swati]
  • A. Swati chosen
    Swati is a Bantu language of the Nguni group, primarily spoken in Eswatini and parts of South Africa.
  • B. Sarayu
    Sarayu is a significant river in northern India, traditionally associated with the ancient city of Ayodhya and revered in Hindu mythology.
  • C. Ranganadi River
    The Ranganadi River is a significant tributary of the Brahmaputra in northeastern India, flowing through Arunachal Pradesh and Assam and supporting irrigation, hydropower, and local ecosystems.
  • D. Amravati
    Amravati is a major city in the Vidarbha region of central India, known as an important commercial and educational center.
  • E. Indravati
    Indravati is a significant river in central India that flows through states like Chhattisgarh and Odisha before joining the Godavari River.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2facf67e0819089a23ce6f5642fbe completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004575157c819098dbf27cf6641ff4 completed May 10, 2026, 8:44 a.m.
Created at: April 10, 2026, 5:07 a.m.