Triple
T16368315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ol' Janx Spirit |
E397492
|
entity |
| Predicate | hasFictionalEffect |
P58963
|
FINISHED |
| Object | severe intoxication |
—
|
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: severe intoxication | Statement: [Ol' Janx Spirit, hasFictionalEffect, severe intoxication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalEffect Context triple: [Ol' Janx Spirit, hasFictionalEffect, severe intoxication]
-
A.
hasFictionalFunction
Indicates that an entity serves a role, purpose, or function within a fictional context or narrative.
-
B.
hasFictionalProperty
chosen
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
-
C.
hasFictionalScope
Indicates that something pertains to, applies within, or is limited to a fictional or imagined context rather than real-world scope.
-
D.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
E.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff3f0694819097faa1c1447a9e97 |
completed | April 18, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:08 a.m.