Triple
T20759046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PureVision |
E510924
|
entity |
| Predicate | targetAnatomicalSite |
P37015
|
FINISHED |
| Object | cornea |
—
|
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: cornea | Statement: [PureVision, targetAnatomicalSite, cornea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAnatomicalSite Context triple: [PureVision, targetAnatomicalSite, cornea]
-
A.
treatsAnatomicalSite
chosen
Indicates that an action, intervention, or agent is directed toward and intended to treat a specific anatomical site.
-
B.
affectsAnatomicalLocation
Indicates that one entity produces an effect on, or has an impact at, a specific anatomical location.
-
C.
nearSiteOf
Indicates that one entity is located in close physical proximity to the site or location associated with another entity.
-
D.
anatomicalFeature
Indicates that one entity is an anatomical part, structure, or feature of another entity.
-
E.
examinesAnatomicalRegion
Indicates that one entity inspects, studies, or evaluates a specific anatomical region of another entity or of a body.
- 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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c24751688190829f9d836abfb606 |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:35 p.m.