Triple
T12841547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | vajra |
E307062
|
entity |
| Predicate | usedByPractitioner |
P37643
|
FINISHED |
| Object | lama |
—
|
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: lama | Statement: [vajra, usedByPractitioner, lama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedByPractitioner Context triple: [vajra, usedByPractitioner, lama]
-
A.
associatedWithPractice
Indicates a relationship in which an entity is connected or linked to a particular practice, activity, or customary way of doing something.
-
B.
practicedMedicineIn
Indicates that a person engaged in the professional practice of medicine within a specified location or jurisdiction.
-
C.
prescribedBy
Indicates that something (typically a treatment, medication, or procedure) has been formally ordered or authorized by a specific agent, usually a medical professional.
-
D.
notablePractitioner
Indicates that an entity is a well-known or distinguished practitioner of a particular field, discipline, or activity.
-
E.
primaryPractitioners
chosen
Indicates the entities that are the main or most directly responsible practitioners of a given activity, field, or practice in relation to another entity.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:35 p.m.