Triple

T2220467
Position Surface form Disambiguated ID Type / Status
Subject Ogooué River E48127 entity
Predicate passesNear P416 FINISHED
Object Lambaréné
Lambaréné is a town in western Gabon best known for its location on the Ogooué River and for hosting the historic Albert Schweitzer Hospital.
 E245957 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: Lambaréné | Statement: [Ogooué River, passesNear, Lambaréné]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lambaréné
Context triple: [Ogooué River, passesNear, Lambaréné]
  • A. Matadi
    Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
  • B. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • C. Bangui
    Bangui is the capital and largest city of the Central African Republic, serving as its political, economic, and cultural center.
  • D. Serekunda
    Serekunda is the most populous urban center and a major commercial hub in The Gambia.
  • E. Malabo
    Malabo is the largest city and main economic and administrative center of Equatorial Guinea, located on the northern coast of Bioko Island in the Gulf of Guinea.
  • 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: Lambaréné
Triple: [Ogooué River, passesNear, Lambaréné]
Generated description
Lambaréné is a town in western Gabon best known for its location on the Ogooué River and for hosting the historic Albert Schweitzer Hospital.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lambaréné
Target entity description: Lambaréné is a town in western Gabon best known for its location on the Ogooué River and for hosting the historic Albert Schweitzer Hospital.
  • A. Matadi
    Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
  • B. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • C. Bangui
    Bangui is the capital and largest city of the Central African Republic, serving as its political, economic, and cultural center.
  • D. Serekunda
    Serekunda is the most populous urban center and a major commercial hub in The Gambia.
  • E. Malabo
    Malabo is the largest city and main economic and administrative center of Equatorial Guinea, located on the northern coast of Bioko Island in the Gulf of Guinea.
  • 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_69ae655df21c8190aa9624f15955c565 completed March 9, 2026, 6:14 a.m.
NEDg Description generation batch_69ae667dede88190b3d1f8bb8866e19e completed March 9, 2026, 6:19 a.m.
NED2 Entity disambiguation (via description) batch_69ae66f12c648190a146de7b2bfdb541 completed March 9, 2026, 6:21 a.m.
Created at: March 4, 2026, 7:46 p.m.