Triple
T24322612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russia and Prussia |
E613008
|
entity |
| Predicate | wereKeyActorsIn |
P15562
|
FINISHED |
| Object | the downfall of the Napoleonic Empire |
—
|
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: the downfall of the Napoleonic Empire | Statement: [Russia and Prussia, wereKeyActorsIn, the downfall of the Napoleonic Empire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wereKeyActorsIn Context triple: [Russia and Prussia, wereKeyActorsIn, the downfall of the Napoleonic Empire]
-
A.
actsIn
Indicates that an entity performs or appears in a creative work, such as a film, play, or show.
-
B.
actúaEn
Indicates that an actor or performer takes part in or appears in a specific production, such as a film, play, or television show.
-
C.
involvedActor
chosen
Indicates that an entity participates as an actor or participant in the referenced event, activity, or situation.
-
D.
oftenPlayedBy
Indicates that one entity frequently performs, portrays, or executes another entity, such as a role, character, or piece of music.
-
E.
associatedWithLeadActorOfFilm
Indicates a relationship where one entity is connected or linked in some relevant way to the lead actor of a specified film.
- 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_69e2d7da491c8190b6e6218af50923db |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f292ad4cc881908794b501cf70b7a1 |
completed | April 29, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69f1c45f45888190a9ccc225906c34bd |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 1:52 a.m.