Triple
T20061732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ABVD regimen |
E499490
|
entity |
| Predicate | hasAdministrationSetting |
P3538
|
FINISHED |
| Object | outpatient oncology clinic |
—
|
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: outpatient oncology clinic | Statement: [ABVD regimen, hasAdministrationSetting, outpatient oncology clinic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdministrationSetting Context triple: [ABVD regimen, hasAdministrationSetting, outpatient oncology clinic]
-
A.
hasSetting
chosen
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
B.
hasUserSetting
Indicates that a user is associated with a specific configuration or preference setting.
-
C.
hasSettingRole
Indicates that an entity participates in a setting by fulfilling a specific contextual or functional role within it.
-
D.
hasAdministrativeType
Indicates that an entity is associated with a specific category or level of administrative classification (such as type of jurisdiction or administrative unit).
-
E.
hasAdministrationSite
Indicates the specific location or site on or in a subject where a substance, treatment, or intervention is administered.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6637601dc8190a07fc20844093cb7 |
completed | April 20, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:38 p.m.