Triple
T8905033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Custom Van |
E212032
|
entity |
| Predicate | isFictionalized |
P14491
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [My Custom Van, isFictionalized, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFictionalized Context triple: [My Custom Van, isFictionalized, true]
-
A.
fictionalizationOf
Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
-
B.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
C.
fictionalizationLevel
Indicates the degree to which an event, account, or representation has been altered, embellished, or invented relative to factual reality.
-
D.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
-
E.
fictionalStatus
chosen
Indicates that an entity exists only in imagination or narrative and does not correspond to a real-world counterpart.
- 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_69ca839255248190b43984294abd92ae |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc64c3d83081909f181bfd601eaf99 |
completed | April 1, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69cc5ecf55248190a29f00fbf99f13c4 |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:55 p.m.