Triple
T29245696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portorosso Cup race |
E741435
|
entity |
| Predicate | antagonistParticipant |
P89676
|
FINISHED |
| Object | Ercole Visconti |
—
|
NE NERFINISHED |
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: Ercole Visconti | Statement: [Portorosso Cup race, antagonistParticipant, Ercole Visconti]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antagonistParticipant Context triple: [Portorosso Cup race, antagonistParticipant, Ercole Visconti]
-
A.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
B.
antagonistActorRole
Indicates that an actor plays the role of an antagonist in a given work or context.
-
C.
antagonistInvolved
chosen
Indicates that an antagonist participates in, influences, or is otherwise actively involved in the referenced event or situation.
-
D.
antagonistStatus
Indicates that an entity holds an opposing or adversarial role, often acting as the main source of conflict relative to another entity or objective.
-
E.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
- 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_69f0911eba2c8190b07cd2fdf91422c9 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f66489459c8190aa343cb2b8af1300 |
completed | May 2, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 12:32 p.m.