Triple

T9269258
Position Surface form Disambiguated ID Type / Status
Subject Angas E222780 entity
Predicate regionOfUse P82 FINISHED
Object Mangu area E360984 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: Mangu area | Statement: [Angas, regionOfUse, Mangu area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mangu area
Context triple: [Angas, regionOfUse, Mangu area]
  • A. Panguna area
    The Panguna area is a region on Bougainville Island in Papua New Guinea known primarily for hosting one of the world’s largest former open-cut copper and gold mines and for its central role in the island’s political and environmental conflicts.
  • B. Mango Pir area
    Mango Pir area is a locality in Karachi known for its historic Sufi shrine of Mangho Pir and its nearby crocodile-inhabited pond, which attracts pilgrims and visitors.
  • C. Mangu chosen
    Mangu is a town and local government area in central Nigeria known for its agricultural activities and ethnic diversity within Plateau State.
  • D. Zona da Mata
    Zona da Mata is a humid, forested coastal region in the Brazilian state of Pernambuco, historically known for its sugarcane plantations and Atlantic Forest remnants.
  • E. Zona da Mata
    Zona da Mata is a historically important, densely populated and economically developed forested region in the eastern part of Minas Gerais, Brazil, known for its coffee production and Atlantic Forest remnants.
  • 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_69ca841ffe208190aa7bcffbef2f8379 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd074ef7408190b213c09491918132 completed April 1, 2026, 11:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09c2239a08190b954c8c57ced8fd2 completed April 4, 2026, 5:05 a.m.
Created at: March 30, 2026, 7:33 p.m.