Triple
T30739111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dom Basaluzzo |
E782644
|
entity |
| Predicate | relationshipTypeWithDoris |
P204186
|
FINISHED |
| Object | platonic |
—
|
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: platonic | Statement: [Dom Basaluzzo, relationshipTypeWithDoris, platonic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithDoris Context triple: [Dom Basaluzzo, relationshipTypeWithDoris, platonic]
-
A.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
relationshipTypeWithSassi
Indicates the specific type or nature of the relationship that an entity has with Sassi.
-
C.
relationshipTypeStart
Indicates the type or category of relationship that begins or is initiated at a specific point or event.
-
D.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
-
E.
relationshipTarget
Indicates that an entity is the object or recipient toward which a specified relationship is directed.
- 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_69f224aeb1588190897d395e8ed2acb8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a034540e37c819087a5c75c559323d8 |
completed | May 12, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_6a0344e26fec8190867227f9692e92df |
completed | May 12, 2026, 3:18 p.m. |
| PDg | Predicate description generation | batch_6a0345400778819081fb3b5b71336cd7 |
completed | May 12, 2026, 3:20 p.m. |
Created at: April 29, 2026, 8:37 p.m.