Triple
T10305828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amy Peterson |
E241756
|
entity |
| Predicate | antagonistFaced |
P18963
|
FINISHED |
| Object | vampire neighbor |
—
|
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: vampire neighbor | Statement: [Amy Peterson, antagonistFaced, vampire neighbor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antagonistFaced Context triple: [Amy Peterson, antagonistFaced, vampire neighbor]
-
A.
antagonistOf
chosen
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
B.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
C.
antagonistInvolved
Indicates that an antagonist participates in, influences, or is otherwise actively involved in the referenced event or situation.
-
D.
portraysAdversary
Indicates that one entity depicts or represents another entity as an opponent, enemy, or rival.
-
E.
primaryAntagonistType
Indicates the role or category of the main opposing force or adversary that serves as the central source of conflict.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:46 a.m.