Triple
T19277284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sicani |
E482089
|
entity |
| Predicate | eventuallyInfluencedBy |
P87217
|
FINISHED |
| Object | Greek culture |
—
|
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: Greek culture | Statement: [Sicani, eventuallyInfluencedBy, Greek culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eventuallyInfluencedBy Context triple: [Sicani, eventuallyInfluencedBy, Greek culture]
-
A.
wereInfluencedBy
chosen
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
-
B.
hadInfluenceOn
Indicates that one entity affected, shaped, or contributed to the development, behavior, or characteristics of another entity.
-
C.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
D.
eventInfluencedBy
Indicates that an event occurs or unfolds in a way that is causally or significantly affected by another entity, factor, or prior event.
-
E.
hasEnduringInfluenceOn
Indicates that one entity exerts a lasting, long-term impact on another entity’s state, development, or behavior.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbbd5f34819086535f28fd880411 |
completed | April 20, 2026, 10:11 a.m. |
| PD | Predicate disambiguation | batch_69e4dd07a7208190afcd51ba1dc87c33 |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:30 p.m.