Triple

T198325
Position Surface form Disambiguated ID Type / Status
Subject IN E4045 entity
Predicate alpha2CodeFor P2261 FINISHED
Object India E1124 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: India | Statement: [IN, alpha2CodeFor, India]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: India
Context triple: [IN, alpha2CodeFor, India]
  • A. India chosen
    India is a large South Asian country known for its vast population, cultural and linguistic diversity, and rapid economic growth.
  • B. Pakistan
    Pakistan is a South Asian country bordering India, Afghanistan, Iran, and China, known for its diverse cultures, strategic geopolitical position, and significant agricultural and nuclear capabilities.
  • C. Gujarat
    Gujarat is a western coastal state of India known for its significant role in trade and industry, rich cultural heritage, and historic cities such as Ahmedabad.
  • D. Indonesia
    Indonesia is a large Southeast Asian nation made up of thousands of islands, known for its diverse cultures, significant natural resources, and status as one of the world’s largest emerging economies.
  • E. Nepal
    Nepal is a landlocked South Asian country in the Himalayas, known for Mount Everest, its rich cultural heritage, and its location between India and China.
  • 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_69a254bca59881909a15e1496f1508c7 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a25bcb2c7c8190b0e031e93651182a completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a389a873d48190ac41ff919027688a completed March 1, 2026, 12:34 a.m.
Created at: Feb. 28, 2026, 2:44 a.m.