Triple
T11279290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Calf for Best Actress |
E267018
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object |
Johanna ter Steege
Johanna ter Steege is a Dutch actress acclaimed for her powerful performances in European cinema and international films.
|
E916865
|
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: Johanna ter Steege | Statement: [Golden Calf for Best Actress, notableRecipient, Johanna ter Steege]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johanna ter Steege Context triple: [Golden Calf for Best Actress, notableRecipient, Johanna ter Steege]
-
A.
Johanna de Jongh
Johanna de Jongh was the wife of Dutch Golden Age painter Jan Asselijn, about whom little is historically documented beyond her marital connection to the artist.
-
B.
Johanna Geilus
Johanna Geilus was the wife of Austrian journalist and politician Fritz Austerlitz.
-
C.
Astrid Nienhuis
Astrid Nienhuis is a Dutch politician who serves as the mayor of the municipality of Heemstede in the Netherlands.
-
D.
Maria van den Boogaard
Maria van den Boogaard was the wife of Dutch politician and former Prime Minister Louis Beel.
-
E.
Maayke Velders
Maayke Velders is known primarily as the spouse of Dutch naval hero Michiel de Ruyter.
- 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: Johanna ter Steege Triple: [Golden Calf for Best Actress, notableRecipient, Johanna ter Steege]
Generated description
Johanna ter Steege is a Dutch actress acclaimed for her powerful performances in European cinema and international films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Johanna ter Steege Target entity description: Johanna ter Steege is a Dutch actress acclaimed for her powerful performances in European cinema and international films.
-
A.
Johanna de Jongh
Johanna de Jongh was the wife of Dutch Golden Age painter Jan Asselijn, about whom little is historically documented beyond her marital connection to the artist.
-
B.
Johanna Geilus
Johanna Geilus was the wife of Austrian journalist and politician Fritz Austerlitz.
-
C.
Astrid Nienhuis
Astrid Nienhuis is a Dutch politician who serves as the mayor of the municipality of Heemstede in the Netherlands.
-
D.
Maria van den Boogaard
Maria van den Boogaard was the wife of Dutch politician and former Prime Minister Louis Beel.
-
E.
Maayke Velders
Maayke Velders is known primarily as the spouse of Dutch naval hero Michiel de Ruyter.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e969b3448190940e2bd499d2d7de |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a0edcd081908547745d16d643ab |
completed | April 19, 2026, 4:59 p.m. |
| NEDg | Description generation | batch_69e510f7bec08190989118b6e4a7fa49 |
completed | April 19, 2026, 5:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5168c8da0819093bf61d8ea5f9e35 |
completed | April 19, 2026, 5:53 p.m. |
Created at: April 8, 2026, 9:31 p.m.