Triple
T20193532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mewtwo |
E493026
|
entity |
| Predicate | alignmentInAnime |
P74485
|
FINISHED |
| Object | Initially antagonistic |
—
|
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: Initially antagonistic | Statement: [Mewtwo, alignmentInAnime, Initially antagonistic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentInAnime Context triple: [Mewtwo, alignmentInAnime, Initially antagonistic]
-
A.
alignmentInSeries
Indicates that one entity’s position or orientation is arranged in a specific way relative to others within an ordered sequence or series.
-
B.
eraAlignment
Indicates that two entities are associated with, or correspond to, the same historical or temporal era.
-
C.
alignmentInStory
chosen
Indicates how a character’s moral or ethical stance (e.g., good, neutral, evil) is portrayed within the context of a specific story.
-
D.
alignmentShape
Indicates that one entity’s shape is arranged, oriented, or matched in position relative to another entity’s shape.
-
E.
alignmentGoal
Indicates that an entity has a desired or target alignment state it aims to achieve or maintain.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad7270081908ed8513a8363e9b1 |
completed | April 20, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e55b11124c8190babacf2a0fe2d057 |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:37 p.m.