Triple

T21746739
Position Surface form Disambiguated ID Type / Status
Subject Claude Simon E536807 entity
Predicate placeOfBirth P1 FINISHED
Object Madagascar NE NERFINISHED

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: [Claude Simon, placeOfBirth, Madagascar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madagascar
Context triple: [Claude Simon, placeOfBirth, Madagascar]
  • A. Madagascar chosen
    Madagascar is a large island nation in the Indian Ocean renowned for its unique biodiversity and high rate of endemic species.
  • B. 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.
  • 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. Ambarikorano, Madagascar
    Ambarikorano, Madagascar is a locality in Madagascar known as the birthplace of the country’s first president, Philibert Tsiranana.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46df5448190b4322127ffc4c690 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01a771b908190886cade242e263e4 completed April 28, 2026, 2:24 a.m.
Created at: April 16, 2026, 6:49 p.m.