Triple
T19164939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilha do Maio |
E469154
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Monte Vermelho
Monte Vermelho is a small settlement located on the island of Maio in Cape Verde.
|
E1361415
|
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: Monte Vermelho | Statement: [Ilha do Maio, hasSettlement, Monte Vermelho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monte Vermelho Context triple: [Ilha do Maio, hasSettlement, Monte Vermelho]
-
A.
Monte Renoso
Monte Renoso is a prominent mountain in southern Corsica, France, known for its rugged terrain and scenic alpine landscapes.
-
B.
Monte Grande
Monte Grande is a suburban city in the Buenos Aires metropolitan area of Argentina, known as the administrative seat of the Esteban Echeverría Partido.
-
C.
Monte Castelo
Monte Castelo is a municipality in the state of Santa Catarina in southern Brazil, known for its rural landscape and small-town character.
-
D.
Serro Ventoso
Serro Ventoso is a civil parish in the municipality of Porto de Mós in central Portugal, known for its rural landscape and proximity to the limestone hills of the Serra de Aire.
-
E.
Monte Semprevisa
Monte Semprevisa is the highest peak of the Monti Lepini range in central Italy, known for its limestone landscapes and panoramic views over the surrounding Lazio region.
- 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: Monte Vermelho Triple: [Ilha do Maio, hasSettlement, Monte Vermelho]
Generated description
Monte Vermelho is a small settlement located on the island of Maio in Cape Verde.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Monte Vermelho Target entity description: Monte Vermelho is a small settlement located on the island of Maio in Cape Verde.
-
A.
Monte Renoso
Monte Renoso is a prominent mountain in southern Corsica, France, known for its rugged terrain and scenic alpine landscapes.
-
B.
Monte Grande
Monte Grande is a suburban city in the Buenos Aires metropolitan area of Argentina, known as the administrative seat of the Esteban Echeverría Partido.
-
C.
Monte Castelo
Monte Castelo is a municipality in the state of Santa Catarina in southern Brazil, known for its rural landscape and small-town character.
-
D.
Serro Ventoso
Serro Ventoso is a civil parish in the municipality of Porto de Mós in central Portugal, known for its rural landscape and proximity to the limestone hills of the Serra de Aire.
-
E.
Monte Semprevisa
Monte Semprevisa is the highest peak of the Monti Lepini range in central Italy, known for its limestone landscapes and panoramic views over the surrounding Lazio region.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f15e2720819084b1707497db26a2 |
completed | April 20, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a06f25ef2208190842d2b29bee2c8ce |
completed | May 15, 2026, 10:15 a.m. |
| NEDg | Description generation | batch_6a06f3864b848190bcc76953e1a261f3 |
completed | May 15, 2026, 10:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a06f4199a588190943d3d45536a228c |
completed | May 15, 2026, 10:23 a.m. |
Created at: April 10, 2026, 12:06 p.m.