Triple
T34197110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Croker's crew |
E877272
|
entity |
| Predicate | hasEthicalAlignmentInFiction |
P120754
|
FINISHED |
| Object | sympathetic criminals |
—
|
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: sympathetic criminals | Statement: [Charlie Croker's crew, hasEthicalAlignmentInFiction, sympathetic criminals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthicalAlignmentInFiction Context triple: [Charlie Croker's crew, hasEthicalAlignmentInFiction, sympathetic criminals]
-
A.
hasAlignmentInFiction
chosen
Indicates that a fictional character, group, or entity possesses a specific moral or ethical alignment within a fictional setting.
-
B.
ethicalStanceInStory
Indicates the ethical position, judgment, or moral viewpoint expressed or taken within the context of a particular story or narrative.
-
C.
hasEthicalText
Indicates that an entity is associated with or contains text expressing ethical principles, guidelines, or considerations.
-
D.
characterAlignment
Indicates the moral or ethical stance a character holds, typically along axes such as good–evil and lawful–chaotic.
-
E.
hasEthicalDimension
Indicates that the relationship, action, or situation involves moral considerations, value judgments, or ethical implications.
- 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_69f349af20a4819089ac24d28f2d8112 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 1, 2026, 1:55 a.m.