Triple
T16400990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbados Labour Party |
E398307
|
entity |
| Predicate | hasChairperson |
P10
|
FINISHED |
| Object |
Verla De Peiza
Verla De Peiza is a Barbadian politician and attorney who has served in prominent leadership roles within Barbados’s major political parties.
|
E1212236
|
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: Verla De Peiza | Statement: [Barbados Labour Party, hasChairperson, Verla De Peiza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verla De Peiza Context triple: [Barbados Labour Party, hasChairperson, Verla De Peiza]
-
A.
Maira Suro
Maira Suro is a television producer best known for her executive production work on the science fiction series "The 4400."
-
B.
Doro Merande
Doro Merande was an American character actress known for her distinctive comic and eccentric roles in mid-20th-century film, television, and theater.
-
C.
Marlen
Marlen is a village district of the town of Kehl in the German state of Baden-Württemberg.
-
D.
Amada Cruz
Amada Cruz is an American museum director and arts administrator known for leading major art institutions, including serving as director of the Seattle Art Museum.
-
E.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
- 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: Verla De Peiza Triple: [Barbados Labour Party, hasChairperson, Verla De Peiza]
Generated description
Verla De Peiza is a Barbadian politician and attorney who has served in prominent leadership roles within Barbados’s major political parties.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Verla De Peiza Target entity description: Verla De Peiza is a Barbadian politician and attorney who has served in prominent leadership roles within Barbados’s major political parties.
-
A.
Maira Suro
Maira Suro is a television producer best known for her executive production work on the science fiction series "The 4400."
-
B.
Doro Merande
Doro Merande was an American character actress known for her distinctive comic and eccentric roles in mid-20th-century film, television, and theater.
-
C.
Marlen
Marlen is a village district of the town of Kehl in the German state of Baden-Württemberg.
-
D.
Amada Cruz
Amada Cruz is an American museum director and arts administrator known for leading major art institutions, including serving as director of the Seattle Art Museum.
-
E.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327cfb2fc8190bbc2765247c4b4e4 |
completed | April 18, 2026, 6:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c5e7b4881908245228730a65876 |
completed | May 10, 2026, 8:05 a.m. |
| NEDg | Description generation | batch_6a003e490bf0819093acd954a4cd9b0c |
completed | May 10, 2026, 8:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a003f1037408190a5edd4a5258b50c9 |
completed | May 10, 2026, 8:17 a.m. |
Created at: April 10, 2026, 5:09 a.m.