Triple
T4303900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Garnier |
E99906
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Garnier
Garnier is a French surname most famously associated with architect Charles Garnier, designer of the Paris Opéra.
|
E429420
|
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: Garnier | Statement: [Charles Garnier, familyName, Garnier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garnier Context triple: [Charles Garnier, familyName, Garnier]
-
A.
Neutrogena
Neutrogena is a widely recognized skincare and cosmetics brand known for its dermatologist-recommended products, including facial cleansers, moisturizers, sunscreens, and acne treatments.
-
B.
Lancôme
Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
-
C.
L'Oréal
L'Oréal is a French multinational cosmetics and beauty company recognized as one of the world’s largest and most influential personal care brands.
-
D.
Herbal Essences
Herbal Essences is a popular hair care brand known for its fragranced shampoos and conditioners often marketed with botanical and natural imagery.
-
E.
Biotherm
Biotherm is a French skincare brand known for its use of aquatic ingredients and scientifically driven formulas for face and body care.
- 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: Garnier Triple: [Charles Garnier, familyName, Garnier]
Generated description
Garnier is a French surname most famously associated with architect Charles Garnier, designer of the Paris Opéra.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Garnier Target entity description: Garnier is a French surname most famously associated with architect Charles Garnier, designer of the Paris Opéra.
-
A.
Neutrogena
Neutrogena is a widely recognized skincare and cosmetics brand known for its dermatologist-recommended products, including facial cleansers, moisturizers, sunscreens, and acne treatments.
-
B.
Lancôme
Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
-
C.
L'Oréal
L'Oréal is a French multinational cosmetics and beauty company recognized as one of the world’s largest and most influential personal care brands.
-
D.
Herbal Essences
Herbal Essences is a popular hair care brand known for its fragranced shampoos and conditioners often marketed with botanical and natural imagery.
-
E.
Biotherm
Biotherm is a French skincare brand known for its use of aquatic ingredients and scientifically driven formulas for face and body care.
- 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350b792608190ac778b79c740256a |
completed | March 12, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c7507f1081909cf737dff00542d9 |
completed | March 14, 2026, 8:38 p.m. |
| NEDg | Description generation | batch_69b5c909b7848190bbe00249e0c9e555 |
completed | March 14, 2026, 8:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5c97117088190972bba5dbc1553f7 |
completed | March 14, 2026, 8:47 p.m. |
Created at: March 12, 2026, 11:09 p.m.