Triple

T36708816
Position Surface form Disambiguated ID Type / Status
Subject paclitaxel E906737 entity
Predicate hasTradeName P24555 FINISHED
Object Onxol
Onxol is a branded formulation of the chemotherapy drug paclitaxel used to treat various cancers such as ovarian, breast, and lung cancer.
E2196292 NE FINISHED

How this triple was built (2 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: Onxol | Statement: [paclitaxel, hasTradeName, Onxol]
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: Onxol
Triple: [paclitaxel, hasTradeName, Onxol]
Generated description
Onxol is a branded formulation of the chemotherapy drug paclitaxel used to treat various cancers such as ovarian, breast, and lung cancer.

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_69f76e73ad108190a5241585f2303e9a completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c81113f88190af2bf0f86492a064 completed May 3, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a382ec49c8190a7dcaac1209b7910 completed June 23, 2026, 7:39 a.m.
NEDg Description generation batch_6a3a3bba39448190a21dc14da0144d49 completed June 23, 2026, 7:54 a.m.
NED2 Entity disambiguation (via description) batch_6a3a3d878b108190bf736f6f39b32874 completed June 23, 2026, 8:02 a.m.
Created at: May 3, 2026, 4:12 p.m.