Triple
T23360626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kilum-Ijim Forest |
E593172
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Oku area
The Oku area is a highland region in Cameroon known for its montane forests, rich biodiversity, and traditional communities surrounding Mount Oku.
|
E1582677
|
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: Oku area | Statement: [Kilum-Ijim Forest, locatedIn, Oku area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oku area Context triple: [Kilum-Ijim Forest, locatedIn, Oku area]
-
A.
Okene area
Okene area is a locality in Kogi State, Nigeria, traditionally recognized as a central homeland of the Ebira people.
-
B.
Bisu-Osokom area
The Bisu-Osokom area is a locality within Obanliku in Cross River State, Nigeria, known for its rural communities and agricultural landscape.
-
C.
Isogo area
The Isogo area is a coastal district in Yokohama, Japan, known for its mix of residential neighborhoods, industrial zones, and waterfront facilities.
-
D.
Utoro area
The Utoro area is a coastal gateway settlement in Shari, Hokkaido, serving as a main tourist base for exploring the Shiretoko Peninsula and its natural attractions.
-
E.
Kujo area
Kujo area is a neighborhood within Osaka’s Nishi Ward known for its mix of residential streets, local shops, and convenient urban access.
- 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: Oku area Triple: [Kilum-Ijim Forest, locatedIn, Oku area]
Generated description
The Oku area is a highland region in Cameroon known for its montane forests, rich biodiversity, and traditional communities surrounding Mount Oku.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oku area Target entity description: The Oku area is a highland region in Cameroon known for its montane forests, rich biodiversity, and traditional communities surrounding Mount Oku.
-
A.
Okene area
Okene area is a locality in Kogi State, Nigeria, traditionally recognized as a central homeland of the Ebira people.
-
B.
Bisu-Osokom area
The Bisu-Osokom area is a locality within Obanliku in Cross River State, Nigeria, known for its rural communities and agricultural landscape.
-
C.
Isogo area
The Isogo area is a coastal district in Yokohama, Japan, known for its mix of residential neighborhoods, industrial zones, and waterfront facilities.
-
D.
Utoro area
The Utoro area is a coastal gateway settlement in Shari, Hokkaido, serving as a main tourist base for exploring the Shiretoko Peninsula and its natural attractions.
-
E.
Kujo area
Kujo area is a neighborhood within Osaka’s Nishi Ward known for its mix of residential streets, local shops, and convenient urban access.
- 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_69e25d24d2a4819092e6ede74c2a918d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0a730f8819088fec53a43b063f8 |
completed | April 29, 2026, 6:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c5dd385948190940cf5b878e54002 |
completed | May 19, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_6a0c5fa0ae848190a23b0c8c16345c26 |
completed | May 19, 2026, 1:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c604cc84c8190946e2a35e0f736ce |
completed | May 19, 2026, 1:06 p.m. |
Created at: April 17, 2026, 5:30 p.m.