Triple
T7693999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Igor |
E174323
|
entity |
| Predicate | usesTreatment |
P78752
|
FINISHED |
| Object | experimental therapy |
—
|
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: experimental therapy | Statement: [Dr. Igor, usesTreatment, experimental therapy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTreatment Context triple: [Dr. Igor, usesTreatment, experimental therapy]
-
A.
hasCommonTreatment
Indicates that two or more entities share at least one treatment method or therapeutic approach in common.
-
B.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
C.
exportTreatment
Indicates the action or process of sending or transferring a treatment (such as a medical, data, or procedural treatment) from one system, location, or context to another for external use or application.
-
D.
treatment
Indicates that one entity is used as a medical or therapeutic intervention to address, manage, or cure a condition affecting another entity.
-
E.
usesDrug
Indicates that an entity consumes, administers, or otherwise makes use of a specified drug.
- F. None of above. chosen
Provenance (4 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
| PDg | Predicate description generation | batch_69c706d0c1708190a3e74523997814b8 |
completed | March 27, 2026, 10:38 p.m. |
Created at: March 27, 2026, 4:02 p.m.