Triple
T6436045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Far North Region |
E129896
|
entity |
| Predicate | containsDepartment |
P1467
|
FINISHED |
| Object |
Mayo-Danay
Mayo-Danay is an administrative department in northern Cameroon known for its predominantly rural communities and proximity to the Chadian border.
|
E593191
|
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: Mayo-Danay | Statement: [Far North Region, containsDepartment, Mayo-Danay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mayo-Danay Context triple: [Far North Region, containsDepartment, Mayo-Danay]
-
A.
Yorba
Yorba is a Spanish-origin surname historically associated with early Californian landowners and the prominent Yorba family in Southern California.
-
B.
Mayo
The Mayo are an Indigenous people of northwestern Mexico, primarily inhabiting the state of Sonora and known for their rich agricultural traditions and ceremonial dances.
-
C.
Mayo
Mayo is a surname most prominently associated with the American medical family that co-founded the Mayo Clinic.
-
D.
Dina
Dina is a feminine given name used in various cultures, often as a variant of names like Dinah or Edina.
-
E.
Naiche
Naiche was the last hereditary chief of the Chiricahua Apache and a prominent leader during the final phase of the Apache resistance against the United States.
- 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: Mayo-Danay Triple: [Far North Region, containsDepartment, Mayo-Danay]
Generated description
Mayo-Danay is an administrative department in northern Cameroon known for its predominantly rural communities and proximity to the Chadian border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mayo-Danay Target entity description: Mayo-Danay is an administrative department in northern Cameroon known for its predominantly rural communities and proximity to the Chadian border.
-
A.
Yorba
Yorba is a Spanish-origin surname historically associated with early Californian landowners and the prominent Yorba family in Southern California.
-
B.
Mayo
The Mayo are an Indigenous people of northwestern Mexico, primarily inhabiting the state of Sonora and known for their rich agricultural traditions and ceremonial dances.
-
C.
Mayo
Mayo is a surname most prominently associated with the American medical family that co-founded the Mayo Clinic.
-
D.
Dina
Dina is a feminine given name used in various cultures, often as a variant of names like Dinah or Edina.
-
E.
Naiche
Naiche was the last hereditary chief of the Chiricahua Apache and a prominent leader during the final phase of the Apache resistance against the United States.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c069622eb881908b40fc8079d312d6 |
completed | March 22, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640f2915c8190aea3578dcd77dd5f |
completed | March 27, 2026, 8:33 a.m. |
| NEDg | Description generation | batch_69c64237ae8881908bbaa2760113da7c |
completed | March 27, 2026, 8:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c64658463c8190a1d68beec15cab3d |
completed | March 27, 2026, 8:56 a.m. |
Created at: March 22, 2026, 4:45 p.m.