Triple
T1379166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Roche-Posay |
E29296
|
entity |
| Predicate | hasProductLine |
P3585
|
FINISHED |
| Object |
Kerium
Kerium is a specialized hair and scalp care product line from La Roche-Posay designed to address issues such as dandruff, sensitivity, and hair thinning.
|
E158638
|
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: Kerium | Statement: [La Roche-Posay, hasProductLine, Kerium]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kerium Context triple: [La Roche-Posay, hasProductLine, Kerium]
-
A.
Kerria
Kerria is a small genus of deciduous flowering shrubs, best known for the ornamental Japanese kerria with its bright yellow, rose-like blooms.
-
B.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
-
C.
Khoni
Khoni is a small town in western Georgia’s Imereti region, known for its historical churches and surrounding natural landscapes.
-
D.
Wonokitri
Wonokitri is a village in East Java, Indonesia, known as a gateway settlement for visitors heading to the Mount Bromo area.
-
E.
Kiloran
Kiloran is a small coastal settlement on the Scottish island of Colonsay, known for its scenic bay and sandy beach.
- 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: Kerium Triple: [La Roche-Posay, hasProductLine, Kerium]
Generated description
Kerium is a specialized hair and scalp care product line from La Roche-Posay designed to address issues such as dandruff, sensitivity, and hair thinning.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kerium Target entity description: Kerium is a specialized hair and scalp care product line from La Roche-Posay designed to address issues such as dandruff, sensitivity, and hair thinning.
-
A.
Kerria
Kerria is a small genus of deciduous flowering shrubs, best known for the ornamental Japanese kerria with its bright yellow, rose-like blooms.
-
B.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
-
C.
Khoni
Khoni is a small town in western Georgia’s Imereti region, known for its historical churches and surrounding natural landscapes.
-
D.
Wonokitri
Wonokitri is a village in East Java, Indonesia, known as a gateway settlement for visitors heading to the Mount Bromo area.
-
E.
Kiloran
Kiloran is a small coastal settlement on the Scottish island of Colonsay, known for its scenic bay and sandy beach.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c3187f248190a5813274b0ef944d |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acd48a48fc81908b156c273cb5dfc0 |
completed | March 8, 2026, 1:44 a.m. |
| NEDg | Description generation | batch_69acd77d879881908decae7056bfd277 |
completed | March 8, 2026, 1:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acd81c7c1081908b65ca5a57f8706e |
completed | March 8, 2026, 1:59 a.m. |
Created at: March 1, 2026, 7:59 p.m.