Triple
T25484386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicholas Garrigan |
E638659
|
entity |
| Predicate | relationshipToIdiAmin |
P10690
|
FINISHED |
| Object | doctor-patient relationship |
—
|
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: doctor-patient relationship | Statement: [Nicholas Garrigan, relationshipToIdiAmin, doctor-patient relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToIdiAmin Context triple: [Nicholas Garrigan, relationshipToIdiAmin, doctor-patient relationship]
-
A.
relationshipToUser
Indicates the type of connection or association an entity has with the current user.
-
B.
identityRelation
Indicates that two entities are in fact the very same entity, not merely similar or equivalent.
-
C.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
-
D.
relationshipToRa
Indicates a specified type of relational connection that an entity has to the entity Ra.
-
E.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
- 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_69e75dbabeac8190bab30628f8b799d4 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
Created at: April 21, 2026, 2:32 p.m.