Triple
T5440898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cornish |
E122128
|
entity |
| Predicate | hasMutationSystem |
P64081
|
FINISHED |
| Object | initial consonant mutation |
—
|
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: initial consonant mutation | Statement: [Cornish, hasMutationSystem, initial consonant mutation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMutationSystem Context triple: [Cornish, hasMutationSystem, initial consonant mutation]
-
A.
hasVariantSystem
Indicates that one system is an alternative or variant form of another system within the same general framework or category.
-
B.
hasAspectSystem
Indicates that an entity possesses or is associated with a particular aspect system, such as a structured set of characteristics, dimensions, or perspectives.
-
C.
hasHumanModification
Indicates that an entity has been altered, influenced, or modified as a result of human activity or intervention.
-
D.
hasTypeSystem
Indicates that an entity employs, is governed by, or is associated with a particular type system (a defined set of rules for classifying and constraining types).
-
E.
hasRegisterSystem
Indicates that an entity uses or is associated with a particular register system (e.g., a system for recording, tracking, or registering items, events, or participants).
- F. None of above. chosen
Provenance (4 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_69bd46400768819092925d461c0b8432 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd922f66bc8190b7d47fd68d2fcf2e |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd919aeb048190b786f814177d6cd9 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd922dc688819092bf33589ebc6d50 |
completed | March 20, 2026, 6:30 p.m. |
Created at: March 20, 2026, 2:07 p.m.