Triple
T24777306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | da Gama |
E619894
|
entity |
| Predicate | meaningOfComponent_da |
P116292
|
FINISHED |
| Object | of the |
—
|
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: of the | Statement: [da Gama, meaningOfComponent_da, of the]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningOfComponent_da Context triple: [da Gama, meaningOfComponent_da, of the]
-
A.
meaningOfComponent_zada
Indicates that one entity represents or defines the meaning or semantic interpretation of a specific component of another entity.
-
B.
meaningComponent
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
C.
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.
-
D.
meaningComponent郎
Indicates that one entity is a semantic component or constituent part of the overall meaning of another entity.
-
E.
xxxxComponentMeaning
chosen
Indicates that one entity represents the meaning, definition, or semantic content of a component of 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_69e2fabd04488190a2d13c97be745a2d |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410d3ea308190ae80cb7d5bf94249 |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:36 a.m.