Triple
T59758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdinand Magellan |
E1184
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object |
Sabrosa
Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
|
E11633
|
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: Sabrosa | Statement: [Ferdinand Magellan, birthPlace, Sabrosa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sabrosa Context triple: [Ferdinand Magellan, birthPlace, Sabrosa]
-
A.
Albufeira
Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
-
B.
Lisbon
Lisbon is the coastal capital city of Portugal, renowned for its historic architecture, hilly landscape, and role as a major cultural and economic center in Europe.
-
C.
Algarve
Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
-
D.
Praia da Oura
Praia da Oura is a popular sandy beach in Portugal’s Algarve region, known for its lively atmosphere, golden cliffs, and proximity to the resort town of Albufeira.
-
E.
Malecón
Malecón is a famous seaside promenade and seawall in Havana, Cuba, known for its ocean views, social life, and historic architecture.
- 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: Sabrosa Triple: [Ferdinand Magellan, birthPlace, Sabrosa]
Generated description
Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sabrosa Target entity description: Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
-
A.
Albufeira
Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
-
B.
Lisbon
Lisbon is the coastal capital city of Portugal, renowned for its historic architecture, hilly landscape, and role as a major cultural and economic center in Europe.
-
C.
Algarve
Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
-
D.
Praia da Oura
Praia da Oura is a popular sandy beach in Portugal’s Algarve region, known for its lively atmosphere, golden cliffs, and proximity to the resort town of Albufeira.
-
E.
Malecón
Malecón is a famous seaside promenade and seawall in Havana, Cuba, known for its ocean views, social life, and historic architecture.
- 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_69a24a552ef88190a0df287d68c65cba |
completed | Feb. 28, 2026, 1:52 a.m. |
| NER | Named-entity recognition | batch_69a24ec5f46081909f3ba0b25190282b |
completed | Feb. 28, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a27bff33b8819084f00ed115ebedeb |
completed | Feb. 28, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_69a27f2f07d88190832000212142b088 |
completed | Feb. 28, 2026, 5:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a27ffd4818819091a276d54c750dc0 |
completed | Feb. 28, 2026, 5:41 a.m. |
Created at: Feb. 28, 2026, 1:55 a.m.