Triple

T623396
Position Surface form Disambiguated ID Type / Status
Subject Saraiki E14560 entity
Predicate region P40 FINISHED
Object South Asia E6055 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: South Asia | Statement: [Saraiki, region, South Asia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: South Asia
Context triple: [Saraiki, region, South Asia]
  • A. South Asia chosen
    South Asia is a culturally and linguistically diverse region of the Asian continent that includes countries such as India, Pakistan, Bangladesh, Nepal, Sri Lanka, Bhutan, and the Maldives.
  • B. Asia
    Asia is a figure in Greek mythology, often considered an Oceanid nymph associated with the region that later bore her name.
  • C. Asia
    Asia is a figure in Greek mythology, often considered one of the Oceanids and associated with the region that later bore her name.
  • D. Asia
    Asia is the world’s largest and most populous continent, encompassing diverse cultures, languages, and landscapes across the Eastern and Northern Hemispheres.
  • E. South-Central Asia
    South-Central Asia is a subregion of Asia that spans the geographic and cultural transition zone between South Asia and Central Asia, encompassing countries like Afghanistan and its neighbors.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e41753881909f0faed720cc31bc completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6732a8c0881909753261f9256fcf2 completed March 3, 2026, 5:35 a.m.
Created at: March 1, 2026, 7:35 p.m.