Triple
T18191861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Marie |
E435554
|
entity |
| Predicate | semanticMeaningComponent_Jean |
P16024
|
FINISHED |
| Object | God is gracious |
—
|
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: God is gracious | Statement: [Jean-Marie, semanticMeaningComponent_Jean, God is gracious]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: semanticMeaningComponent_Jean Context triple: [Jean-Marie, semanticMeaningComponent_Jean, God is gracious]
-
A.
meaningComponent
chosen
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
B.
objectMeaning
Indicates that one entity represents, expresses, or conveys the meaning or semantic content of another entity.
-
C.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
D.
meaningComponent郎
Indicates that one entity is a semantic component or constituent part of the overall meaning of another entity.
-
E.
meaningComponent_mar
Indicates that something is a semantic or conceptual component contributing to the overall meaning of another item, such as a word, phrase, or expression.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d05974819094b4a50d081be881 |
completed | April 19, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.