Triple
T18709649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Thomas Becker |
E457465
|
entity |
| Predicate | usesTreatmentMethod |
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. Thomas Becker, usesTreatmentMethod, experimental therapy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTreatmentMethod Context triple: [Dr. Thomas Becker, usesTreatmentMethod, experimental therapy]
-
A.
usesTreatment
chosen
Indicates that one entity applies or employs a particular treatment or therapeutic method on or for another entity.
-
B.
hasCommonTreatment
Indicates that two or more entities share at least one treatment method or therapeutic approach in common.
-
C.
hasReceivedTreatmentFor
Indicates that an entity has undergone or been given a treatment in relation to a specified condition, issue, or problem.
-
D.
knownForTreatmentOf
Indicates that an entity is recognized or notable for providing treatment or medical care for a particular condition, disease, or type of patient.
-
E.
treatmentType
Indicates the specific kind or category of treatment applied or prescribed in relation to an entity or condition.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671a3c8c81909466bf5d81477a37 |
completed | April 19, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69e478e0889c8190a118d67b200ce8ef |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:50 a.m.