Triple

T15014610
Position Surface form Disambiguated ID Type / Status
Subject Pleurodira E377925 entity
Predicate notableRegion P22 FINISHED
Object Madagascar E27635 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: Madagascar | Statement: [Pleurodira, notableRegion, Madagascar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madagascar
Context triple: [Pleurodira, notableRegion, Madagascar]
  • A. Madagascar
    Madagascar is a 2005 animated comedy film produced by DreamWorks Animation that follows a group of Central Park Zoo animals who find themselves stranded on the island of Madagascar.
  • B. Madagascar chosen
    Madagascar is a large island nation in the Indian Ocean renowned for its unique biodiversity and high rate of endemic species.
  • C. Mauritius
    Mauritius is an island nation in the Indian Ocean known for its multicultural society, stable democracy, and tourism-driven economy.
  • D. Mauricius
    Mauricius is a Latin given name of Roman origin that later evolved into various European forms such as Maurice and Morris.
  • E. Seychelles
    Seychelles is an Indian Ocean island nation off the coast of East Africa, known for its tropical beaches, coral reefs, and unique biodiversity.
  • 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_69d85cd3a3c881908c71fc424d459c17 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7623c3c819092ca36b358b01842 completed April 15, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dce8240819097efddb43b79ad4b completed May 9, 2026, 2:37 a.m.
Created at: April 10, 2026, 2:55 a.m.