Triple

T17044516
Position Surface form Disambiguated ID Type / Status
Subject Tom McGrath E413529 entity
Predicate voiceActedIn P9616 FINISHED
Object Madagascar E297725 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: [Tom McGrath, voiceActedIn, Madagascar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madagascar
Context triple: [Tom McGrath, voiceActedIn, Madagascar]
  • A. Madagascar
    Madagascar is a large island nation in the Indian Ocean renowned for its unique biodiversity and high rate of endemic species.
  • B. Madagascar chosen
    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. 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_69d886cd18288190b006abab23f811b7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3da9c112c81908232dc6908d831cf completed April 18, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01413eba788190982351a97286e81f completed May 11, 2026, 2:38 a.m.
Created at: April 10, 2026, 5:33 a.m.