Triple

T2220470
Position Surface form Disambiguated ID Type / Status
Subject Ogooué River E48127 entity
Predicate passesNear P416 FINISHED
Object Ndjolé
Ndjolé is a town in central Gabon that serves as an important river port and transport hub along the Ogooué River.
E249100 NE FINISHED

How this triple was built (4 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: Ndjolé | Statement: [Ogooué River, passesNear, Ndjolé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ndjolé
Context triple: [Ogooué River, passesNear, Ndjolé]
  • A. Langoué Baï
    Langoué Baï is a renowned forest clearing in Gabon celebrated for its rich biodiversity and frequent gatherings of forest elephants and other wildlife.
  • B. Sikasso
    Sikasso is a major city in southern Mali known as an important agricultural and commercial center near the borders with Burkina Faso and Côte d'Ivoire.
  • C. Lelekou
    Lelekou is the birth surname of renowned Greek actress and singer Irene Papas.
  • D. Maroua
    Maroua is a prominent city in northern Cameroon known as a regional commercial and cultural center near the Sahel.
  • E. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ndjolé
Triple: [Ogooué River, passesNear, Ndjolé]
Generated description
Ndjolé is a town in central Gabon that serves as an important river port and transport hub along the Ogooué River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ndjolé
Target entity description: Ndjolé is a town in central Gabon that serves as an important river port and transport hub along the Ogooué River.
  • A. Langoué Baï
    Langoué Baï is a renowned forest clearing in Gabon celebrated for its rich biodiversity and frequent gatherings of forest elephants and other wildlife.
  • B. Sikasso
    Sikasso is a major city in southern Mali known as an important agricultural and commercial center near the borders with Burkina Faso and Côte d'Ivoire.
  • C. Lelekou
    Lelekou is the birth surname of renowned Greek actress and singer Irene Papas.
  • D. Maroua
    Maroua is a prominent city in northern Cameroon known as a regional commercial and cultural center near the Sahel.
  • E. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • F. None of above. chosen

Provenance (5 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_69a88aa1ee708190862c8c378c41e9eb completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc01386588190a9507f2969a201ca completed March 7, 2026, 6:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6afc6dd881909dd51d8a18ab4c74 completed March 9, 2026, 6:38 a.m.
NEDg Description generation batch_69ae6ef1de2881908c7967c52b5c9db8 completed March 9, 2026, 6:55 a.m.
NED2 Entity disambiguation (via description) batch_69ae6f4281508190b9e00155a3a68773 completed March 9, 2026, 6:57 a.m.
Created at: March 4, 2026, 7:46 p.m.