Triple

T11184203
Position Surface form Disambiguated ID Type / Status
Subject Louise-Hélène Autard de Bragard E264618 entity
Predicate placeOfBirth P1 FINISHED
Object Mauritius E28590 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: Mauritius | Statement: [Louise-Hélène Autard de Bragard, placeOfBirth, Mauritius]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mauritius
Context triple: [Louise-Hélène Autard de Bragard, placeOfBirth, Mauritius]
  • A. Mauritius chosen
    Mauritius is an island nation in the Indian Ocean known for its multicultural society, stable democracy, and tourism-driven economy.
  • B. Mauricius
    Mauricius is a Latin given name of Roman origin that later evolved into various European forms such as Maurice and Morris.
  • C. Seychelles
    Seychelles is an Indian Ocean island nation off the coast of East Africa, known for its tropical beaches, coral reefs, and unique biodiversity.
  • D. Madagascar
    Madagascar is a large island nation in the Indian Ocean renowned for its unique biodiversity and high rate of endemic species.
  • E. 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.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8a9c5e081908c85b41a268428fb completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e483c1b4f88190b7c38b254d37c7fb completed April 19, 2026, 7:26 a.m.
Created at: April 8, 2026, 9:29 p.m.