Triple
T21211320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanley Ipkiss |
E522726
|
entity |
| Predicate | alignmentInOriginalComics |
P143569
|
FINISHED |
| Object | anti-hero |
—
|
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: anti-hero | Statement: [Stanley Ipkiss, alignmentInOriginalComics, anti-hero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentInOriginalComics Context triple: [Stanley Ipkiss, alignmentInOriginalComics, anti-hero]
-
A.
alignmentInStory
Indicates how a character’s moral or ethical stance (e.g., good, neutral, evil) is portrayed within the context of a specific story.
-
B.
originallyAlignedWith
Indicates that an entity was initially in agreement, support, or association with another entity or group, regardless of any later changes in stance or affiliation.
-
C.
alignmentInSeries
Indicates that one entity’s position or orientation is arranged in a specific way relative to others within an ordered sequence or series.
-
D.
alignmentAtIntroduction
Indicates that two entities share a particular alignment or stance at the moment one is first introduced.
-
E.
eraAlignment
Indicates that two entities are associated with, or correspond to, the same historical or temporal era.
- 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_69e0b511ed84819099b449b4a111085c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7346eb20c8190aeb3c0cc0a24aaf9 |
completed | April 21, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5fa92a2448190896c022dd27511ad |
completed | April 20, 2026, 10:06 a.m. |
Created at: April 16, 2026, 3:37 p.m.