Triple
T5134467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duchy of Aquitaine |
E115785
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Aunis
Aunis was a historic coastal province in western France centered around the port city of La Rochelle.
|
E496848
|
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: Aunis | Statement: [Duchy of Aquitaine, contains, Aunis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aunis Context triple: [Duchy of Aquitaine, contains, Aunis]
-
A.
Greuze
Greuze is a French surname most famously associated with Jean-Baptiste Greuze, an 18th-century painter known for his sentimental and moralizing genre scenes.
-
B.
Catroux
Catroux is a French surname most notably borne by Georges Catroux, a prominent French general and diplomat of the 20th century.
-
C.
Aulon
Aulon is the historical name of the coastal city now known as Vlorë in southern Albania, an important port with ancient Greek and Roman roots.
-
D.
Falconet
Falconet is a French surname most notably associated with Étienne-Maurice Falconet, an 18th-century sculptor renowned for works such as the Bronze Horseman statue of Peter the Great in Saint Petersburg.
-
E.
Maurus
Maurus is a masculine given name of Latin origin, historically associated with early Christian saints and used as a variant of names like Maurice.
- 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: Aunis Triple: [Duchy of Aquitaine, contains, Aunis]
Generated description
Aunis was a historic coastal province in western France centered around the port city of La Rochelle.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aunis Target entity description: Aunis was a historic coastal province in western France centered around the port city of La Rochelle.
-
A.
Greuze
Greuze is a French surname most famously associated with Jean-Baptiste Greuze, an 18th-century painter known for his sentimental and moralizing genre scenes.
-
B.
Catroux
Catroux is a French surname most notably borne by Georges Catroux, a prominent French general and diplomat of the 20th century.
-
C.
Aulon
Aulon is the historical name of the coastal city now known as Vlorë in southern Albania, an important port with ancient Greek and Roman roots.
-
D.
Falconet
Falconet is a French surname most notably associated with Étienne-Maurice Falconet, an 18th-century sculptor renowned for works such as the Bronze Horseman statue of Peter the Great in Saint Petersburg.
-
E.
Maurus
Maurus is a masculine given name of Latin origin, historically associated with early Christian saints and used as a variant of names like Maurice.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd784e306081908dd8317227227807 |
completed | March 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4cd5e188190b1404cefc887e0b3 |
completed | March 21, 2026, 4:18 p.m. |
| NEDg | Description generation | batch_69bec571d5948190b659a7b5038f8bdd |
completed | March 21, 2026, 4:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bec973e71c8190a9c043389d627156 |
completed | March 21, 2026, 4:38 p.m. |
Created at: March 20, 2026, 1:43 p.m.