Triple
T31140020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revelation by Artemis |
E793754
|
entity |
| Predicate | revealsCauseOfEvents |
P122823
|
FINISHED |
| Object | Aphrodite’s vengeance |
—
|
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: Aphrodite’s vengeance | Statement: [Revelation by Artemis, revealsCauseOfEvents, Aphrodite’s vengeance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: revealsCauseOfEvents Context triple: [Revelation by Artemis, revealsCauseOfEvents, Aphrodite’s vengeance]
-
A.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
B.
causeInStory
chosen
Indicates that one event, action, or state functions as the cause of another within the narrative structure of a story.
-
C.
focusesOnCause
Indicates that an action, explanation, or analysis is directed toward identifying, examining, or emphasizing the underlying cause of something.
-
D.
disasterCauseDetail
Indicates a detailed explanation of the specific cause or contributing factors behind a disaster.
-
E.
causesFeaturesIn
Indicates that one entity is responsible for producing, giving rise to, or bringing about specific characteristics or features in another entity.
- 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_69f224d2b3a48190aa9dd26fbf6eab1a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c234d648190a243fb2b107136a9 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:05 p.m.