Triple

T1379159
Position Surface form Disambiguated ID Type / Status
Subject La Roche-Posay E29296 entity
Predicate hasProductLine P3585 FINISHED
Object Lipikar
Lipikar is La Roche-Posay’s dermatological body-care line formulated to hydrate, protect, and soothe dry to very dry and sensitive skin.
 E158633 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: Lipikar | Statement: [La Roche-Posay, hasProductLine, Lipikar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lipikar
Context triple: [La Roche-Posay, hasProductLine, Lipikar]
  • A. Lipara
    Lipara is one of the Hesperides, the nymphs of Greek mythology associated with the evening and the golden apples of the gods.
  • B. Rakai Pikatan
    Rakai Pikatan was a 9th-century Javanese king of the Medang (Mataram) Kingdom, known for consolidating royal power in Central Java and patronizing major Hindu temple construction.
  • C. Sivaraksa
    Sivaraksa is the surname of Sulak Sivaraksa, a prominent Thai social activist, intellectual, and proponent of engaged Buddhism.
  • D. Ledaal
    Ledaal is a historic manor house in Stavanger, Norway, that has served as a royal residence and cultural landmark.
  • E. Inkeri
    Inkeri refers to the Ingrian Finns, a Finnic ethnic group historically inhabiting the Ingria region near Saint Petersburg in northwestern Russia.
  • 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: Lipikar
Triple: [La Roche-Posay, hasProductLine, Lipikar]
Generated description
Lipikar is La Roche-Posay’s dermatological body-care line formulated to hydrate, protect, and soothe dry to very dry and sensitive skin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lipikar
Target entity description: Lipikar is La Roche-Posay’s dermatological body-care line formulated to hydrate, protect, and soothe dry to very dry and sensitive skin.
  • A. Lipara
    Lipara is one of the Hesperides, the nymphs of Greek mythology associated with the evening and the golden apples of the gods.
  • B. Rakai Pikatan
    Rakai Pikatan was a 9th-century Javanese king of the Medang (Mataram) Kingdom, known for consolidating royal power in Central Java and patronizing major Hindu temple construction.
  • C. Sivaraksa
    Sivaraksa is the surname of Sulak Sivaraksa, a prominent Thai social activist, intellectual, and proponent of engaged Buddhism.
  • D. Ledaal
    Ledaal is a historic manor house in Stavanger, Norway, that has served as a royal residence and cultural landmark.
  • E. Inkeri
    Inkeri refers to the Ingrian Finns, a Finnic ethnic group historically inhabiting the Ingria region near Saint Petersburg in northwestern Russia.
  • 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.