Triple
T8223883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carola Schouten |
E192130
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Carola
Carola is a Dutch politician known for serving as Deputy Prime Minister and Minister of Agriculture, Nature and Food Quality in the Netherlands.
|
E719569
|
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: Carola | Statement: [Carola Schouten, givenName, Carola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carola Context triple: [Carola Schouten, givenName, Carola]
-
A.
Lorena
Lorena is a city in the state of São Paulo, Brazil, known for hosting a campus of the University of São Paulo.
-
B.
Winona
Winona is a historic river city in southeastern Minnesota known for its Mississippi River bluffs, cultural festivals, and regional educational institutions.
-
C.
Tonina
Tonina is an ancient Maya archaeological site in Chiapas, Mexico, known for its towering acropolis, intricate relief sculptures, and significant role in Classic-period Maya politics.
-
D.
Carla
Carla is a feminine given name commonly used in various languages, often considered the female form of Carl or Charles.
-
E.
Claretta
Claretta was the nickname of Claretta Petacci, the Italian mistress of dictator Benito Mussolini who was executed alongside him in 1945.
- 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: Carola Triple: [Carola Schouten, givenName, Carola]
Generated description
Carola is a Dutch politician known for serving as Deputy Prime Minister and Minister of Agriculture, Nature and Food Quality in the Netherlands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Carola Target entity description: Carola is a Dutch politician known for serving as Deputy Prime Minister and Minister of Agriculture, Nature and Food Quality in the Netherlands.
-
A.
Lorena
Lorena is a city in the state of São Paulo, Brazil, known for hosting a campus of the University of São Paulo.
-
B.
Winona
Winona is a historic river city in southeastern Minnesota known for its Mississippi River bluffs, cultural festivals, and regional educational institutions.
-
C.
Tonina
Tonina is an ancient Maya archaeological site in Chiapas, Mexico, known for its towering acropolis, intricate relief sculptures, and significant role in Classic-period Maya politics.
-
D.
Carla
Carla is a feminine given name commonly used in various languages, often considered the female form of Carl or Charles.
-
E.
Claretta
Claretta was the nickname of Claretta Petacci, the Italian mistress of dictator Benito Mussolini who was executed alongside him in 1945.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb77cc351481908d7dcd6d3d15d59f |
completed | March 31, 2026, 7:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccee0fd9d0819094350c9c7887cabe |
completed | April 1, 2026, 10:06 a.m. |
| NEDg | Description generation | batch_69ccf1bc720081908c4eabf58336318a |
completed | April 1, 2026, 10:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd05f26f9c8190a3cc00c03c6dda95 |
completed | April 1, 2026, 11:48 a.m. |
Created at: March 30, 2026, 5:45 p.m.