Triple
T19928697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | מְפִיבֹשֶׁת |
E478994
|
entity |
| Predicate | nurse |
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: [מְפִיבֹשֶׁת, nurse, unnamed nurse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nurse Context triple: [מְפִיבֹשֶׁת, nurse, unnamed nurse]
-
A.
hasNurse
chosen
Indicates that an entity is assigned or associated with a nurse who provides care or medical support to it.
-
B.
nursingBehavior
Indicates a caregiving relationship in which one entity provides nursing care or nurturing support to another.
-
C.
clinicalRole
Indicates the specific function, responsibility, or position an entity holds within a clinical or healthcare context.
-
D.
caregiverOf
Indicates a relationship where one entity provides ongoing care, support, or supervision for another entity’s well-being.
-
E.
née
Indicates that a person’s original birth name, typically a maiden name, is being specified before it was changed (for example, by marriage).
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659cd4500819090363a4b7d6bf193 |
completed | April 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.