Triple

T10794276
Position Surface form Disambiguated ID Type / Status
Subject Ogooué-Ivindo Province E254662 entity
Predicate capital P234 FINISHED
Object Makokou E245955 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: Makokou | Statement: [Ogooué-Ivindo Province, capital, Makokou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makokou
Context triple: [Ogooué-Ivindo Province, capital, Makokou]
  • A. Makokou chosen
    Makokou is a small town in northeastern Gabon that serves as a key access point to the surrounding rainforest and protected areas.
  • B. Goura
    Goura is a small village in the Peloponnese region of Greece, known for its traditional stone architecture and mountainous surroundings.
  • C. Moukari
    Moukari is a Finnish amateur radio callsign holder, identified by the callsign K9FIN Moukari.
  • D. Garoua
    Garoua is a major city in northern Cameroon that serves as an important commercial and administrative center and a key hub for river and overland transport in the region.
  • E. Yokadouma
    Yokadouma is a town in eastern Cameroon that serves as an important local administrative and commercial center near the country's forested border regions.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d732f878648190be5e25c56a7511cf completed April 9, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69de84f1fdfc8190a31a13ae434e56c1 completed April 14, 2026, 6:18 p.m.
Created at: April 8, 2026, 9:17 p.m.