Triple
T28793409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tubero |
E727019
|
entity |
| Predicate | hasViewpointOn |
P93193
|
FINISHED |
| Object | mixed constitution |
—
|
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: mixed constitution | Statement: [Tubero, hasViewpointOn, mixed constitution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewpointOn Context triple: [Tubero, hasViewpointOn, mixed constitution]
-
A.
hasViewpointConcept
Indicates that something is associated with, characterized by, or defined through a particular viewpoint, perspective, or conceptual stance.
-
B.
hasViewingPointFor
Indicates that one entity serves as a vantage point or location from which another entity can be viewed or observed.
-
C.
hasViewpointType
Indicates that something is associated with or characterized by a particular type or category of viewpoint or perspective.
-
D.
hasViewpointStatus
chosen
Indicates that an entity holds a particular evaluative or perspectival status (e.g., stance, opinion, or viewpoint classification) with respect to something.
-
E.
isMajorViewpointOf
Indicates that a particular perspective, opinion, or interpretation is a primary or widely recognized way of viewing or understanding something.
- 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_69f0319b7c44819085736bcc256185e6 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 28, 2026, 6:24 a.m.