Triple
T10738627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Männerpension |
E253260
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Ingrid van Bergen
Ingrid van Bergen is a German actress known for her extensive film and television career since the 1950s, often portraying strong, charismatic women.
|
E883193
|
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: Ingrid van Bergen | Statement: [Männerpension, hasCastMember, Ingrid van Bergen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ingrid van Bergen Context triple: [Männerpension, hasCastMember, Ingrid van Bergen]
-
A.
Astrid Nienhuis
Astrid Nienhuis is a Dutch politician who serves as the mayor of the municipality of Heemstede in the Netherlands.
-
B.
Sjoukje Ozinga
Sjoukje Ozinga was the mother of Saskia van Uylenburgh, the Dutch woman best known as the wife and muse of painter Rembrandt van Rijn.
-
C.
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.
-
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: Ingrid van Bergen Triple: [Männerpension, hasCastMember, Ingrid van Bergen]
Generated description
Ingrid van Bergen is a German actress known for her extensive film and television career since the 1950s, often portraying strong, charismatic women.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ingrid van Bergen Target entity description: Ingrid van Bergen is a German actress known for her extensive film and television career since the 1950s, often portraying strong, charismatic women.
-
A.
Astrid Nienhuis
Astrid Nienhuis is a Dutch politician who serves as the mayor of the municipality of Heemstede in the Netherlands.
-
B.
Sjoukje Ozinga
Sjoukje Ozinga was the mother of Saskia van Uylenburgh, the Dutch woman best known as the wife and muse of painter Rembrandt van Rijn.
-
C.
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.
-
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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710424d8c81908ee9b59d622f2af5 |
completed | April 9, 2026, 2:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de22ed6edc8190beb76bd2971c7cec |
completed | April 14, 2026, 11:20 a.m. |
| NEDg | Description generation | batch_69de25d25474819081402b75ef7492f6 |
completed | April 14, 2026, 11:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69de2808244c8190bdb2d4d49f30e0d7 |
completed | April 14, 2026, 11:42 a.m. |
Created at: April 8, 2026, 9:14 p.m.