Triple
T1887784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magic Cauldron |
E41800
|
entity |
| Predicate | supportsViewpoint |
P13323
|
FINISHED |
| Object | open-source can be economically rational |
—
|
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: open-source can be economically rational | Statement: [Magic Cauldron, supportsViewpoint, open-source can be economically rational]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsViewpoint Context triple: [Magic Cauldron, supportsViewpoint, open-source can be economically rational]
-
A.
supportsView
Indicates that one entity provides the capability to display, render, or present another entity in a particular view or format.
-
B.
viewpointFrom
Indicates a relationship where something is observed, depicted, or described from the perspective or location of a particular entity or point.
-
C.
hasViewpointType
Indicates that something is associated with or characterized by a particular type or category of viewpoint or perspective.
-
D.
supportsPosition
chosen
Indicates that one entity endorses, upholds, or provides backing for the stance, viewpoint, or role represented by another entity.
-
E.
supportsValue
Indicates that one entity provides justification, evidence, or backing for the truth, relevance, or appropriateness of a particular value associated with 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb121a3cc81909c60ac65627142d1 |
completed | March 7, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69abafe61bc48190ac9ead027df930e1 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.