Triple
T5029415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upside Down |
E113258
|
entity |
| Predicate | relationToRealWorld |
P11529
|
FINISHED |
| Object | parallel dimension |
—
|
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: parallel dimension | Statement: [Upside Down, relationToRealWorld, parallel dimension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToRealWorld Context triple: [Upside Down, relationToRealWorld, parallel dimension]
-
A.
influencedByRealWorldConcept
Indicates that something is shaped, inspired, or determined by an existing concept, phenomenon, or principle from the real world.
-
B.
relationshipToWorld
chosen
Indicates how an entity is connected or related to the broader world or external environment.
-
C.
includesPhysicalWorld
Indicates that one entity encompasses, contains, or incorporates aspects or elements of the physical world within its scope or definition.
-
D.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
-
E.
representsInRelationsWith
Indicates that an entity serves as a representative or proxy for another entity within a specified relationship or set of relationships.
- 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_69bd443775e48190a646ffbfc4334723 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd739099a0819099c6201d4e1c5ee2 |
completed | March 20, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69bd71509e9c8190a60c1d8d04936a12 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:36 p.m.