Triple
T5606998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger & Gallet |
E147257
|
entity |
| Predicate | hasProductLine |
P3585
|
FINISHED |
| Object |
Fleur de Figuier
Fleur de Figuier is a fig-inspired fragrance and body care line known for its fresh, fruity, and subtly floral scent profile.
|
E536933
|
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: Fleur de Figuier | Statement: [Roger & Gallet, hasProductLine, Fleur de Figuier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fleur de Figuier Context triple: [Roger & Gallet, hasProductLine, Fleur de Figuier]
-
A.
Frangula
Frangula is a genus of flowering shrubs and small trees, commonly known as buckthorns, found in temperate regions and valued for their ecological and medicinal properties.
-
B.
Rosier
Rosier is a surname of French origin borne by various notable individuals across different fields.
-
C.
Malva
Malva is a genus of flowering plants commonly known as mallows, characterized by their showy, five-petaled flowers and widespread distribution in temperate regions.
-
D.
l’Unifolié
l’Unifolié is the French nickname for the Canadian national flag, highlighting its single red maple leaf on a white background.
-
E.
Mallow
Mallow is a town in north County Cork, Ireland, known historically as a market and spa town on the River Blackwater.
- 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: Fleur de Figuier Triple: [Roger & Gallet, hasProductLine, Fleur de Figuier]
Generated description
Fleur de Figuier is a fig-inspired fragrance and body care line known for its fresh, fruity, and subtly floral scent profile.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fleur de Figuier Target entity description: Fleur de Figuier is a fig-inspired fragrance and body care line known for its fresh, fruity, and subtly floral scent profile.
-
A.
Frangula
Frangula is a genus of flowering shrubs and small trees, commonly known as buckthorns, found in temperate regions and valued for their ecological and medicinal properties.
-
B.
Rosier
Rosier is a surname of French origin borne by various notable individuals across different fields.
-
C.
Malva
Malva is a genus of flowering plants commonly known as mallows, characterized by their showy, five-petaled flowers and widespread distribution in temperate regions.
-
D.
l’Unifolié
l’Unifolié is the French nickname for the Canadian national flag, highlighting its single red maple leaf on a white background.
-
E.
Mallow
Mallow is a town in north County Cork, Ireland, known historically as a market and spa town on the River Blackwater.
- 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020fbb8748190841e5e09db3feef1 |
completed | March 22, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d4465388190b28f47f11e133b6a |
completed | March 22, 2026, 8:12 p.m. |
| NEDg | Description generation | batch_69c04e88680c8190845723f52c060fb7 |
completed | March 22, 2026, 8:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c04f7b889c81909db7cb4baf40ed80 |
completed | March 22, 2026, 8:22 p.m. |
Created at: March 22, 2026, 3:39 p.m.