Triple
T38345092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange Days |
E1041516
|
entity |
| Predicate | characterDisabilityDepicted |
P101225
|
FINISHED |
| Object | hearing impairment |
—
|
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: hearing impairment | Statement: [Orange Days, characterDisabilityDepicted, hearing impairment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterDisabilityDepicted Context triple: [Orange Days, characterDisabilityDepicted, hearing impairment]
-
A.
portraysCharacterWithDisability
chosen
Indicates that an entity depicts or represents a character who has a disability.
-
B.
hasDisabilityRepresentation
Indicates that something includes, portrays, or accounts for the presence and experiences of people with disabilities.
-
C.
fictionalDisability
Indicates that an entity has a disability that exists only in fictional or imaginary contexts, rather than in real-world medical or social classifications.
-
D.
starsPersonWithDisability
Indicates that a work features a person with a disability in a starring or prominently featured role.
-
E.
causeOfDisability
Indicates that one entity is the reason or source that brings about another entity’s disability.
- 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_69f76e2ad95481908c920c0e5c1c3e26 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a0019b0e9fc81909494320f05e81742 |
completed | May 10, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_6a00193379e0819096d1985686ce10e3 |
completed | May 10, 2026, 5:35 a.m. |
Created at: May 3, 2026, 4:30 p.m.