Triple
T25189222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dirk Diggler Story |
E630816
|
entity |
| Predicate | hasFictionalPornName |
P83029
|
FINISHED |
| Object | Dirk Diggler |
—
|
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: Dirk Diggler | Statement: [The Dirk Diggler Story, hasFictionalPornName, Dirk Diggler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalPornName Context triple: [The Dirk Diggler Story, hasFictionalPornName, Dirk Diggler]
-
A.
hasFictionalAlias
chosen
Indicates that an entity is known by an alternative name or identity within a fictional context.
-
B.
isGivenNameOfFictionalCharacter
Indicates that a given name is the personal name borne by a fictional character.
-
C.
canBeFictionalCharacterName
Indicates that something is suitable or valid to be used as the name of a fictional character.
-
D.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
E.
hasFictionalContent
Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
- 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_69e75a8a6d088190ba1e82a4345225e7 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 21, 2026, 12:44 p.m.