Triple

T36599158
Position Surface form Disambiguated ID Type / Status
Subject ERBB3 E902873 entity
Predicate isDrugTarget P149282 FINISHED
Object monoclonal antibodies against HER3 LITERAL 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: monoclonal antibodies against HER3 | Statement: [ERBB3, isDrugTarget, monoclonal antibodies against HER3]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isDrugTarget
Context triple: [ERBB3, isDrugTarget, monoclonal antibodies against HER3]
  • A. isTherapeuticTargetIn chosen
    Indicates that a biological entity (e.g., gene, protein, pathway) is used or proposed as a therapeutic target within a specified disease, condition, or treatment context.
  • B. hasMolecularTarget
    Indicates that one entity (such as a drug or compound) is directed toward, binds to, or specifically interacts with a particular molecular target (such as a protein, receptor, or gene).
  • C. hasDrugBankID
    Indicates that an entity is associated with a specific identifier from the DrugBank database.
  • D. targetsProtein
    Indicates that one entity is directed toward, binds to, or is intended to affect a specific protein as its primary molecular target.
  • E. regulatoryTarget
    Indicates that one entity is subject to control, influence, or governance by another entity under a regulatory or rule-based framework.
  • F. None of above.

Provenance (3 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_69f76e66b7b88190848f7a3e1188915f completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c371931c8190afb1d4dd5157f92c completed May 3, 2026, 9:51 p.m.
PD Predicate disambiguation batch_69f7c1baf25c8190a78dd54a400d2c50 completed May 3, 2026, 9:44 p.m.
Created at: May 3, 2026, 4:11 p.m.