Triple
T25158618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Multiverse (Michael Moorcock) |
E626380
|
entity |
| Predicate | includesLocationType |
P36978
|
FINISHED |
| Object | planes of existence |
—
|
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: planes of existence | Statement: [Multiverse (Michael Moorcock), includesLocationType, planes of existence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesLocationType Context triple: [Multiverse (Michael Moorcock), includesLocationType, planes of existence]
-
A.
includesAreaType
chosen
Indicates that one entity encompasses or contains another entity of a specified area type within its scope or boundaries.
-
B.
includedTerritoryType
Indicates that one territory type is contained within, or forms part of, another territory type.
-
C.
subjectLocationType
Indicates the type or category of location associated with the subject in the relationship.
-
D.
includedSpecialRegionType
Indicates that a special or designated region is included within another region or context, specifying the type of that included special region.
-
E.
hasLocationRole
Indicates that an entity holds or plays a specific role in relation to a particular location (e.g., origin, destination, storage site, or operational area).
- 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_69e2ff2834ec8190b0872e2ec3d76023 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 18, 2026, 6:31 a.m.