Triple
T26916374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ambroise Paré |
E677526
|
entity |
| Predicate | usedTreatment |
P78752
|
FINISHED |
| Object | ligature of arteries instead of cauterization |
—
|
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: ligature of arteries instead of cauterization | Statement: [Ambroise Paré, usedTreatment, ligature of arteries instead of cauterization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedTreatment Context triple: [Ambroise Paré, usedTreatment, ligature of arteries instead of cauterization]
-
A.
usesTreatment
chosen
Indicates that one entity applies or employs a particular treatment or therapeutic method on or for another entity.
-
B.
hasReceivedTreatmentFor
Indicates that an entity has undergone or been given a treatment in relation to a specified condition, issue, or problem.
-
C.
treatment
Indicates that one entity is used as a medical or therapeutic intervention to address, manage, or cure a condition affecting another entity.
-
D.
treatmentType
Indicates the specific kind or category of treatment applied or prescribed in relation to an entity or condition.
-
E.
hasCommonTreatment
Indicates that two or more entities share at least one treatment method or therapeutic approach in common.
- 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_69eee9bdebc48190ba90a12a63e09c73 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 6:04 a.m.