Triple
T27103203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Von Drake's House of Genius |
E686494
|
entity |
| Predicate | hasFictionalHost |
P174471
|
FINISHED |
| Object | Professor Ludwig Von Drake |
—
|
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: Professor Ludwig Von Drake | Statement: [Von Drake's House of Genius, hasFictionalHost, Professor Ludwig Von Drake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalHost Context triple: [Von Drake's House of Genius, hasFictionalHost, Professor Ludwig Von Drake]
-
A.
isFictionalCharacterHost
chosen
Indicates that one entity serves as the host or presenter in a context involving a fictional character.
-
B.
hostsFictional
Indicates that one entity serves as the setting, platform, or environment in which a fictional character, event, or work is situated or presented.
-
C.
hasFictionalSpokesperson
Indicates that an entity is represented or promoted by a spokesperson who is a fictional or imaginary character.
-
D.
hasFictionalPerformer
Indicates that an entity is associated with a performer who is a fictional or imaginary character rather than a real person.
-
E.
hasFictionalCoStar
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
- 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_69ef1489f8b481908e24a1985982bd26 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f791cc969c8190bf187d6031a030d5 |
completed | May 3, 2026, 6:19 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
Created at: April 27, 2026, 8:49 a.m.