Triple

T1295063
Position Surface form Disambiguated ID Type / Status
Subject Madagascar E27635 entity
Predicate largestCity P235 FINISHED
Object Antananarivo E131488 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: Antananarivo | Statement: [Madagascar, largestCity, Antananarivo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antananarivo
Context triple: [Madagascar, largestCity, Antananarivo]
  • A. Antananarivo chosen
    Antananarivo is the capital and largest city of Madagascar, serving as its political, economic, and cultural center.
  • B. Port Louis
    Port Louis is the capital and largest city of Mauritius, serving as its main economic, political, and cultural center as well as a key regional port in the Indian Ocean.
  • C. Masvingo
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • D. Mutare
    Mutare is a major city in eastern Zimbabwe, serving as the capital of Manicaland Province and an important commercial and transport hub near the border with Mozambique.
  • E. Roseau
    Roseau is the largest city and main commercial and administrative center of the Caribbean island nation of Dominica.
  • 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_69a496d6682881909ba658f1c1e0e2b0 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0f4031481908f5e3a53d8a72929 completed March 1, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69acb300d3a0819081a9d19ea1fbdfe2 completed March 7, 2026, 11:21 p.m.
Created at: March 1, 2026, 7:51 p.m.