Triple
T784908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Verde Islands |
E16579
|
entity |
| Predicate | majorIsland |
P756
|
FINISHED |
| Object |
Fogo
Fogo is a volcanic island in Cape Verde known for its active stratovolcano Pico do Fogo and dramatic mountainous landscapes.
|
E93776
|
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: Fogo | Statement: [Cape Verde Islands, majorIsland, Fogo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fogo Context triple: [Cape Verde Islands, majorIsland, Fogo]
-
A.
Fuego
Fuego is an active stratovolcano in Guatemala known for its frequent explosive eruptions and dramatic ash plumes.
-
B.
Lapa
Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
-
C.
Fiambalá
Fiambalá is a small town in northwestern Argentina known for its high-altitude vineyards, desert landscapes, and nearby Andean mountain passes.
-
D.
Terra da Garoa
Terra da Garoa is a popular nickname for the Brazilian metropolis of São Paulo, alluding to its characteristic light, misty rain.
-
E.
Orongo
Orongo is a ceremonial stone village and archaeological site on Easter Island, best known for its role in the Birdman cult and its dramatic clifftop setting overlooking the ocean.
- 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: Fogo Triple: [Cape Verde Islands, majorIsland, Fogo]
Generated description
Fogo is a volcanic island in Cape Verde known for its active stratovolcano Pico do Fogo and dramatic mountainous landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fogo Target entity description: Fogo is a volcanic island in Cape Verde known for its active stratovolcano Pico do Fogo and dramatic mountainous landscapes.
-
A.
Fuego
Fuego is an active stratovolcano in Guatemala known for its frequent explosive eruptions and dramatic ash plumes.
-
B.
Lapa
Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
-
C.
Fiambalá
Fiambalá is a small town in northwestern Argentina known for its high-altitude vineyards, desert landscapes, and nearby Andean mountain passes.
-
D.
Terra da Garoa
Terra da Garoa is a popular nickname for the Brazilian metropolis of São Paulo, alluding to its characteristic light, misty rain.
-
E.
Orongo
Orongo is a ceremonial stone village and archaeological site on Easter Island, best known for its role in the Birdman cult and its dramatic clifftop setting overlooking the ocean.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a76b0d6c8190a09b1a0bd4a6eeec |
completed | March 1, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a6787eac608190acc40d56f827284e |
completed | March 3, 2026, 5:58 a.m. |
| NEDg | Description generation | batch_69a67a663f6c819084b5dffdde3531aa |
completed | March 3, 2026, 6:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a67b1d50b0819088232ad797babced |
completed | March 3, 2026, 6:09 a.m. |
Created at: March 1, 2026, 7:37 p.m.