Triple
T37905583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Arcane Empire |
E945535
|
entity |
| Predicate | hasPotentialAntagonists |
P17627
|
FINISHED |
| Object | rival magical powers |
—
|
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: rival magical powers | Statement: [Spanish Arcane Empire, hasPotentialAntagonists, rival magical powers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPotentialAntagonists Context triple: [Spanish Arcane Empire, hasPotentialAntagonists, rival magical powers]
-
A.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
B.
hasAntagonistGroup
chosen
Indicates that an entity is opposed or challenged by a specific group acting as its antagonist.
-
C.
hasAntagonistForm
Indicates that an entity possesses or takes on a form characterized by opposition, hostility, or antagonistic behavior toward another entity.
-
D.
canSpareAntagonist
Indicates that one entity is able and willing to refrain from harming, defeating, or otherwise eliminating an opposing or hostile entity.
-
E.
hasCommonEnemies
Indicates that two or more entities share at least one enemy in common.
- 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_69fff4530f908190afe9387f732c2b7e |
completed | May 10, 2026, 2:58 a.m. |
| PD | Predicate disambiguation | batch_69fff3c01a64819091196875b0c88607 |
completed | May 10, 2026, 2:56 a.m. |
Created at: May 3, 2026, 4:20 p.m.