Triple
T16092954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calheta (Maio) |
E390402
|
entity |
| Predicate | hasIslandCapital |
P20917
|
FINISHED |
| Object |
Vila do Maio
Vila do Maio is the main town and administrative center of Maio Island in Cape Verde, known for its coastal setting and role as the island’s primary hub.
|
E1194974
|
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: Vila do Maio | Statement: [Calheta (Maio), hasIslandCapital, Vila do Maio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vila do Maio Context triple: [Calheta (Maio), hasIslandCapital, Vila do Maio]
-
A.
Vila Flor
Vila Flor is a municipality in northern Portugal, situated in the Douro region known for its wine production and scenic landscapes.
-
B.
Vila Viçosa
Vila Viçosa is a historic town in Portugal renowned for its marble quarries and as a former residence of the Portuguese royal family.
-
C.
Vila Prudente
Vila Prudente is a metro station in São Paulo, Brazil, serving as a key terminal and transfer point on the city’s rapid transit network.
-
D.
Vila Facaia
Vila Facaia is a civil parish located in the municipality of Pedrógão Grande in central Portugal.
-
E.
Vila Belmiro
Vila Belmiro is the historic home stadium of Santos FC in Santos, Brazil, renowned as one of the most traditional football grounds in the country.
- 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: Vila do Maio Triple: [Calheta (Maio), hasIslandCapital, Vila do Maio]
Generated description
Vila do Maio is the main town and administrative center of Maio Island in Cape Verde, known for its coastal setting and role as the island’s primary hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vila do Maio Target entity description: Vila do Maio is the main town and administrative center of Maio Island in Cape Verde, known for its coastal setting and role as the island’s primary hub.
-
A.
Vila Flor
Vila Flor is a municipality in northern Portugal, situated in the Douro region known for its wine production and scenic landscapes.
-
B.
Vila Viçosa
Vila Viçosa is a historic town in Portugal renowned for its marble quarries and as a former residence of the Portuguese royal family.
-
C.
Vila Prudente
Vila Prudente is a metro station in São Paulo, Brazil, serving as a key terminal and transfer point on the city’s rapid transit network.
-
D.
Vila Facaia
Vila Facaia is a civil parish located in the municipality of Pedrógão Grande in central Portugal.
-
E.
Vila Belmiro
Vila Belmiro is the historic home stadium of Santos FC in Santos, Brazil, renowned as one of the most traditional football grounds in the country.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1858ed09881909bde122971d95753 |
completed | April 17, 2026, 12:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb973c88819091fe284420088e7e |
completed | May 10, 2026, 2:21 a.m. |
| NEDg | Description generation | batch_69ffed3d57388190a4d0faa58ee2a27b |
completed | May 10, 2026, 2:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffedfb88a881909e6adbb3a372246b |
completed | May 10, 2026, 2:31 a.m. |
Created at: April 10, 2026, 4:59 a.m.