Triple
T30098503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Claudas |
E764930
|
entity |
| Predicate | indirectlyAffects |
P54036
|
FINISHED |
| Object | upbringing of Lancelot |
—
|
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: upbringing of Lancelot | Statement: [King Claudas, indirectlyAffects, upbringing of Lancelot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: indirectlyAffects Context triple: [King Claudas, indirectlyAffects, upbringing of Lancelot]
-
A.
indirectImpactOn
chosen
Indicates that one entity affects another entity’s state, condition, or outcome through one or more intermediate factors rather than through a direct interaction.
-
B.
affectsRelationshipBetween
Indicates that one entity causes a change or influence on the nature, quality, or status of the relationship between two or more other entities.
-
C.
alsoAffects
Indicates that an action, condition, or change impacting one entity additionally impacts another entity as well.
-
D.
indirectlyConnects
Indicates that one entity is connected to another through one or more intermediate entities or links, rather than by a direct connection.
-
E.
hasDirectEffect
Indicates that one entity produces an immediate and unmediated impact or change on 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_69f22474e4288190b5f895fe3974aa92 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67d92dbdc8190ae3e8f67b979cb5c |
completed | May 2, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:08 p.m.