Triple
T4904675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mephibosheth |
E109885
|
entity |
| Predicate | hasNurse |
P60573
|
FINISHED |
| Object | unnamed nurse |
—
|
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: unnamed nurse | Statement: [Mephibosheth, hasNurse, unnamed nurse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNurse Context triple: [Mephibosheth, hasNurse, unnamed nurse]
-
A.
hasMedicalStaffApprox
Indicates that an entity is associated with an approximate or estimated number of medical staff.
-
B.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
C.
hasHealthcareProvider
Indicates that one entity receives healthcare services or medical oversight from another entity acting as its healthcare provider.
-
D.
hasClerk
Indicates that an entity is served, assisted, or managed by a clerk associated with it.
-
E.
hasWarden
Indicates that one entity serves as the warden or supervisory authority responsible for another entity.
- F. None of above. chosen
Provenance (4 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd7060f9988190afdf98eb0a38515d |
completed | March 20, 2026, 4:05 p.m. |
Created at: March 20, 2026, 1:29 p.m.