Triple

T1263622
Position Surface form Disambiguated ID Type / Status
Subject Solomon Islands E12553 entity
Predicate hasIsland P970 FINISHED
Object Makira E57264 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: Makira | Statement: [Solomon Islands, hasIsland, Makira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makira
Context triple: [Solomon Islands, hasIsland, Makira]
  • A. Makira chosen
    Makira is a large, rugged island in the Solomon Islands known for its rich biodiversity, traditional Melanesian cultures, and relatively undeveloped, rainforest-covered interior.
  • B. Inga
    Inga is the given first name of American rapper and actress Foxy Brown, whose full name is Inga DeCarlo Fung Marchand.
  • C. Bagassa
    Bagassa is a small genus of tropical trees in the mulberry family, known for species such as Bagassa guianensis found in South American rainforests.
  • D. Gouania
    Gouania is a genus of flowering plants in the buckthorn family, comprising mostly tropical climbing shrubs and vines.
  • E. Dandaka forest
    Dandaka forest is a vast and perilous wilderness in the Indian epic Ramayana, where Rama, Sita, and Lakshmana spend much of their exile and encounter demons and sages.
  • 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_69a4933352e08190ac617291985e76c0 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bfc8d6908190a5b2cf1051cc6d5e completed March 1, 2026, 10:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac9984c21c8190a1cec6c9d2df217a completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:50 p.m.