Triple
T2232341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | See No Evil, Hear No Evil |
E49196
|
entity |
| Predicate | featuresCharacterWithDisability |
P23263
|
FINISHED |
| Object | blind protagonist |
—
|
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: blind protagonist | Statement: [See No Evil, Hear No Evil, featuresCharacterWithDisability, blind protagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCharacterWithDisability Context triple: [See No Evil, Hear No Evil, featuresCharacterWithDisability, blind protagonist]
-
A.
hasSupportingCharacterTrait
Indicates that a supporting character possesses a particular trait, quality, or characteristic.
-
B.
featuresCharacterRole
chosen
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
C.
usesCharacter
Indicates that one entity employs, incorporates, or relies on a particular character (such as a symbol, letter, or persona) in its form, function, or representation.
-
D.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
E.
featuresCharactersFrom
Indicates that one entity (such as a work or production) includes or presents characters originating from another entity.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc06d26bc8190a85ddb6312d2df08 |
completed | March 7, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69abbdadbb0c8190b3a1ede31b8acbfa |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.