Triple
T38246305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LASIK |
E1013898
|
entity |
| Predicate | anesthesiaType |
P97019
|
FINISHED |
| Object | topical anesthesia |
—
|
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: topical anesthesia | Statement: [LASIK, anesthesiaType, topical anesthesia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: anesthesiaType Context triple: [LASIK, anesthesiaType, topical anesthesia]
-
A.
performedFirstEtherAnesthesiaOn
Indicates that the subject was the first to administer ether anesthesia to the object.
-
B.
requiresSedation
Indicates that performing the associated action or procedure necessitates sedating the involved entity (typically a patient).
-
C.
operatedInTheatre
Indicates that a medical or surgical procedure was performed on a patient within an operating theatre or surgical suite.
-
D.
isLessInvasiveThan
Indicates that one procedure, method, or action causes less physical intrusion, disruption, or harm than another when compared.
-
E.
sedationProfile
chosen
Indicates the characteristic pattern or level of sedation associated with an entity, such as how strongly, how long, or in what manner it produces or maintains sedation.
- 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_69f76dd7e89c8190b7866bc85aea521b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcc3321ef081908023590ba70ba0cf |
completed | May 7, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fdc6e08190b05e894c59481a0d |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:30 p.m.