Triple
T783572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Emmanuel of Belgium |
E16552
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Emmanuel
Emmanuel is a Belgian prince, a member of the royal family of Belgium and the son of King Philippe and Queen Mathilde.
|
E105254
|
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: Emmanuel | Statement: [Prince Emmanuel of Belgium, givenName, Emmanuel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emmanuel Context triple: [Prince Emmanuel of Belgium, givenName, Emmanuel]
-
A.
Immanuel
Immanuel is the given name of the influential German philosopher Immanuel Kant, a central figure in modern Western philosophy.
-
B.
Emanuel
Emanuel is a surname most prominently associated with Rahm Emanuel, the American politician and former mayor of Chicago.
-
C.
Simeon
Simeon is a biblical figure, one of the twelve sons of Jacob and a progenitor of one of the tribes of Israel.
-
D.
Johannes
Johannes is the given first name of Paul Kruger, the prominent 19th-century Boer leader and president of the South African Republic.
-
E.
Théodore
Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
- 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: Emmanuel Triple: [Prince Emmanuel of Belgium, givenName, Emmanuel]
Generated description
Emmanuel is a Belgian prince, a member of the royal family of Belgium and the son of King Philippe and Queen Mathilde.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Emmanuel Target entity description: Emmanuel is a Belgian prince, a member of the royal family of Belgium and the son of King Philippe and Queen Mathilde.
-
A.
Immanuel
Immanuel is the given name of the influential German philosopher Immanuel Kant, a central figure in modern Western philosophy.
-
B.
Emanuel
Emanuel is a surname most prominently associated with Rahm Emanuel, the American politician and former mayor of Chicago.
-
C.
Simeon
Simeon is a biblical figure, one of the twelve sons of Jacob and a progenitor of one of the tribes of Israel.
-
D.
Johannes
Johannes is the given first name of Paul Kruger, the prominent 19th-century Boer leader and president of the South African Republic.
-
E.
Théodore
Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7686d0881908c2a4395059be02c |
completed | March 1, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c00c1db48190906a02bb80fe98dc |
completed | March 4, 2026, 5:15 a.m. |
| NEDg | Description generation | batch_69a7c13f15848190b126bdc434953a22 |
completed | March 4, 2026, 5:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7c21dd42881908ac19fed7454d7a9 |
completed | March 4, 2026, 5:24 a.m. |
Created at: March 1, 2026, 7:37 p.m.