Triple
T4160611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Röntgen radiation |
E91523
|
entity |
| Predicate | hasApplicationField |
P14571
|
FINISHED |
| Object | medicine |
—
|
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: medicine | Statement: [Röntgen radiation, hasApplicationField, medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApplicationField Context triple: [Röntgen radiation, hasApplicationField, medicine]
-
A.
hasApp
chosen
Indicates that an entity possesses, provides, or is associated with a particular application.
-
B.
supportsField
Indicates that one entity provides the necessary structure, stability, or backing for a particular field, area, or domain associated with another entity.
-
C.
hasInfield
Indicates that an entity possesses or includes a designated infield area, typically within a larger spatial or structural context.
-
D.
hasFieldName
Indicates that one entity is associated with, or identified by, a specific field name in a data structure or schema.
-
E.
fieldPresence
Indicates that a particular field or attribute exists or is present within a given context, object, or dataset.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0321eee88190871c1d4bf44a5007 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018dc90c8190a754b1bfbc802e80 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:44 p.m.