Triple
T38238011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed Wynn as Albert Dussell |
E1013675
|
entity |
| Predicate | portraysPersonalityTraits |
P192151
|
FINISHED |
| Object | fussy |
—
|
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: fussy | Statement: [Ed Wynn as Albert Dussell, portraysPersonalityTraits, fussy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysPersonalityTraits Context triple: [Ed Wynn as Albert Dussell, portraysPersonalityTraits, fussy]
-
A.
portraysRoleTrait
Indicates that one entity depicts or represents a particular role or character trait of another entity.
-
B.
portraysPersonAs
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
C.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
D.
portraysMainCharacter
Indicates that one entity depicts or represents another entity as the primary or central character in a work or narrative.
-
E.
hasPersonalityDescribedAs
chosen
Indicates that an entity possesses a personality characterized or labeled in a particular way.
- 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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffc3f0b19c8190b5a749bc3cad21dd |
completed | May 9, 2026, 11:32 p.m. |
| PD | Predicate disambiguation | batch_69ffc1b882808190932b2d43ea5537c9 |
completed | May 9, 2026, 11:22 p.m. |
Created at: May 3, 2026, 4:30 p.m.