Triple
T29900131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paradox Engine |
E759385
|
entity |
| Predicate | cardTextFocus |
P77291
|
FINISHED |
| Object | untapping nonland permanents |
—
|
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: untapping nonland permanents | Statement: [Paradox Engine, cardTextFocus, untapping nonland permanents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cardTextFocus Context triple: [Paradox Engine, cardTextFocus, untapping nonland permanents]
-
A.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
-
B.
importFocus
Indicates that attention, priority, or emphasis is being brought into or concentrated on a particular entity or aspect.
-
C.
focusShift
Indicates a change in attention or emphasis from one entity or topic to another.
-
D.
stateOfFocus
chosen
Indicates the particular subject, area, or activity that an entity is currently concentrating attention or effort on.
-
E.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
- 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_69f2245f1cf88190978c70d1a1d2cb73 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6772e14d48190a9c4dda3d35d0f37 |
completed | May 2, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:06 p.m.