Triple
T32538741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | modern France |
E831658
|
entity |
| Predicate | influencedWorldHistoryThrough |
P4749
|
FINISHED |
| Object | French Revolution |
—
|
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: French Revolution | Statement: [modern France, influencedWorldHistoryThrough, French Revolution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedWorldHistoryThrough Context triple: [modern France, influencedWorldHistoryThrough, French Revolution]
-
A.
historicalImpact
chosen
Indicates the influence or lasting effects that an entity, event, or action has had on subsequent history or historical developments.
-
B.
hasHistoricalInfluenceFrom
Indicates that one entity’s characteristics, development, or significance have been shaped or affected by the past actions, ideas, or legacy of another entity.
-
C.
hadInfluenceOn
Indicates that one entity affected, shaped, or contributed to the development, behavior, or characteristics of another entity.
-
D.
hasHistoricalWritingInfluenceFrom
Indicates that one entity’s historical writing style, content, or traditions are influenced by those of another entity.
-
E.
centuryOfGreatestInfluence
Indicates the century during which an entity exerted its greatest impact or influence.
- 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_69f34924b1cc8190ad3aca0c0f012a7e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 1, 2026, 1:02 a.m.