Triple
T34780211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Dedmon |
E1002634
|
entity |
| Predicate | fictionalPortrayalOf |
P198175
|
FINISHED |
| Object | Donald Dedmon |
—
|
NE NERFINISHED |
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: Donald Dedmon | Statement: [Donald Dedmon, fictionalPortrayalOf, Donald Dedmon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalPortrayalOf Context triple: [Donald Dedmon, fictionalPortrayalOf, Donald Dedmon]
-
A.
fictionalPortrayalSubject
Indicates that one entity is the subject or topic being portrayed, depicted, or represented in a fictional work by another entity.
-
B.
portraysFictionalized
Indicates that one entity represents or depicts another entity in a fictionalized or altered manner, rather than as a strictly accurate portrayal.
-
C.
fictionalizationOf
Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
-
D.
portrayedFictionalVersionOf
Indicates that one entity depicted or acted as a fictionalized or altered version of another entity.
-
E.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69feced53a7c819098ec474fb7d514b0 |
completed | May 9, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69fecd9cd5288190aac8b4e04a7ee78e |
completed | May 9, 2026, 6:01 a.m. |
| PDg | Predicate description generation | batch_69feced436a48190b761db7df2d6b6bd |
completed | May 9, 2026, 6:06 a.m. |
Created at: May 3, 2026, 3:59 p.m.