Triple
T5086384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maccus |
E114646
|
entity |
| Predicate | hasDerivationType |
P12825
|
FINISHED |
| Object | patronymic root for surnames |
—
|
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: patronymic root for surnames | Statement: [Maccus, hasDerivationType, patronymic root for surnames]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDerivationType Context triple: [Maccus, hasDerivationType, patronymic root for surnames]
-
A.
derivationType
chosen
Indicates the specific manner or process by which one entity is derived or obtained from another.
-
B.
hasDerivative
Indicates that one entity is derived, obtained, or produced from another through some transformation, process, or modification.
-
C.
hasDerivatives
Indicates that one entity is derived, obtained, or developed from another entity.
-
D.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
E.
hasTypeGenus
Indicates that one entity is the type genus that formally defines or represents the taxonomic group of the other 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_69bd443e941881908eb4e8c685b6f656 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd751fb6dc8190be674c92a17e8c0e |
completed | March 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69bd7159adc881909effd4382c395c66 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:40 p.m.