Triple
T37508070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anima Conductor |
E932147
|
entity |
| Predicate | upgradeLevelCount |
P189410
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Anima Conductor, upgradeLevelCount, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: upgradeLevelCount Context triple: [Anima Conductor, upgradeLevelCount, 5]
-
A.
raisedLevelCapFrom
Indicates that an entity has increased a previously existing maximum level limit from a specified lower value.
-
B.
raisesLevelCapTo
Indicates that one entity increases the maximum allowable level of another entity to a specified value.
-
C.
upgradeType
Indicates the specific kind or category of improvement or enhancement applied to an entity relative to its previous state.
-
D.
upgradeEffect
Indicates that one entity causes an improvement or enhancement in the capabilities, performance, or status of another entity.
-
E.
upgradeTargetUnits
Indicates that certain units are designated to be improved or converted to a higher or more advanced version.
- 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_69f76ec5268481909ea01c73aeeefd42 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbbc48b75c8190bec27dd4b7de797f |
completed | May 6, 2026, 10:10 p.m. |
Created at: May 3, 2026, 4:17 p.m.