Triple
T37904915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Macroverse Empire |
E945519
|
entity |
| Predicate | hasNarrativeUse |
P115762
|
FINISHED |
| Object | worldbuilding backdrop |
—
|
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: worldbuilding backdrop | Statement: [Spanish Macroverse Empire, hasNarrativeUse, worldbuilding backdrop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNarrativeUse Context triple: [Spanish Macroverse Empire, hasNarrativeUse, worldbuilding backdrop]
-
A.
useInNarrative
chosen
Indicates that something is employed as an element or device within a narrative or story.
-
B.
hasNarrative
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
-
C.
hasNarrativeContext
Indicates that an entity is associated with, or situated within, a particular narrative or storytelling context that frames its meaning or role.
-
D.
hasNarrativeRole
Indicates that an entity participates in a narrative with a specific functional role (e.g., protagonist, antagonist, narrator) relative to the story.
-
E.
containsNarrativeOf
Indicates that one entity includes or presents the story, account, or narrative content of another entity.
- 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_69f76ef20bb0819088b5b6ceecb0b8fc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ffb1218cb08190a814c7f0833501a7 |
completed | May 9, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69ffb083d6988190b2757e0cfd629b75 |
completed | May 9, 2026, 10:09 p.m. |
Created at: May 3, 2026, 4:20 p.m.