Triple
T12643409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Countess Emma Luana of Orange-Nassau |
E301956
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object |
Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg
Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg is a Dutch countess and member of the extended Dutch royal family.
|
E996352
|
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: Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg | Statement: [Countess Emma Luana of Orange-Nassau, fullName, Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg Context triple: [Countess Emma Luana of Orange-Nassau, fullName, Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg]
-
A.
Princess Anna of Orange-Nassau
Princess Anna of Orange-Nassau was an 18th-century Dutch princess of the House of Orange-Nassau, notable as the daughter of Anne, Princess Royal of Great Britain, and a member of the broader European royal network.
-
B.
Princess Amalia of Orange-Nassau
Princess Amalia of Orange-Nassau was an 18th-century Dutch princess of the House of Orange, known for her role in European dynastic alliances and courtly life in the Netherlands.
-
C.
Princess Sophie of the Netherlands
Princess Sophie of the Netherlands was a 19th-century Dutch royal who became Grand Duchess of Saxe-Weimar-Eisenach through marriage and was known for her intellectual interests and patronage of the arts.
-
D.
Princess Catharina-Amalia of the Netherlands
Princess Catharina-Amalia of the Netherlands is the heir apparent to the Dutch throne and the eldest daughter of King Willem-Alexander and Queen Máxima.
-
E.
Frederica Louise Wilhelmina of Orange-Nassau
Frederica Louise Wilhelmina of Orange-Nassau was a Dutch princess of the House of Orange-Nassau who became Duchess of Brunswick-Wolfenbüttel through marriage.
- 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: Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg Triple: [Countess Emma Luana of Orange-Nassau, fullName, Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg]
Generated description
Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg is a Dutch countess and member of the extended Dutch royal family.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg Target entity description: Emma Luana Ninette Sophie van Oranje-Nassau van Amsberg is a Dutch countess and member of the extended Dutch royal family.
-
A.
Princess Anna of Orange-Nassau
Princess Anna of Orange-Nassau was an 18th-century Dutch princess of the House of Orange-Nassau, notable as the daughter of Anne, Princess Royal of Great Britain, and a member of the broader European royal network.
-
B.
Princess Amalia of Orange-Nassau
Princess Amalia of Orange-Nassau was an 18th-century Dutch princess of the House of Orange, known for her role in European dynastic alliances and courtly life in the Netherlands.
-
C.
Princess Sophie of the Netherlands
Princess Sophie of the Netherlands was a 19th-century Dutch royal who became Grand Duchess of Saxe-Weimar-Eisenach through marriage and was known for her intellectual interests and patronage of the arts.
-
D.
Princess Catharina-Amalia of the Netherlands
Princess Catharina-Amalia of the Netherlands is the heir apparent to the Dutch throne and the eldest daughter of King Willem-Alexander and Queen Máxima.
-
E.
Frederica Louise Wilhelmina of Orange-Nassau
Frederica Louise Wilhelmina of Orange-Nassau was a Dutch princess of the House of Orange-Nassau who became Duchess of Brunswick-Wolfenbüttel through marriage.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9614bf2f881909976becdf747f4fb |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6687770388190b4777885dae8a38f |
completed | May 2, 2026, 9:11 p.m. |
| NEDg | Description generation | batch_69f669f69fe4819097dfc63780e8587e |
completed | May 2, 2026, 9:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f66b619c88819098acbfb60fac9921 |
completed | May 2, 2026, 9:23 p.m. |
Created at: April 9, 2026, 5:17 p.m.