Triple
T21453418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhamnusia |
E529274
|
entity |
| Predicate | emphasizesAspectOfNemesis |
P132985
|
FINISHED |
| Object | personification of retribution |
—
|
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: personification of retribution | Statement: [Rhamnusia, emphasizesAspectOfNemesis, personification of retribution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emphasizesAspectOfNemesis Context triple: [Rhamnusia, emphasizesAspectOfNemesis, personification of retribution]
-
A.
nemesisMeaning
Indicates that one entity is the arch-enemy or long-standing adversary of another.
-
B.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
C.
wrathfulAspectOf
chosen
Indicates that one entity is a fierce, anger-driven or punitive manifestation or form of another entity.
-
D.
antagonistAttribute
Indicates that an entity possesses a characteristic or role specifically associated with being an antagonist in a narrative or conflict.
-
E.
focusesOnVillain
Indicates that the primary attention, narrative emphasis, or activity is directed toward a villain as the central subject.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d50b88819081a771596d0a2b2b |
completed | April 23, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:07 p.m.