Triple
T2981032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pe |
E80509
|
entity |
| Predicate | hasStrokeType |
P44440
|
FINISHED |
| Object | consonantal |
—
|
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: consonantal | Statement: [Pe, hasStrokeType, consonantal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrokeType Context triple: [Pe, hasStrokeType, consonantal]
-
A.
hasStrokeOrder
Indicates that there is a specific, ordered sequence of strokes used to write or draw the related symbol or character.
-
B.
hasStageType
Indicates that an entity is associated with, or classified by, a specific type or category of stage within a process, lifecycle, or workflow.
-
C.
hasSternType
Indicates that an entity (typically a vessel) possesses a specific type or design of stern.
-
D.
hasCapitalType
Indicates that a specified location’s capital is of a particular type (e.g., political, administrative, or economic capital).
-
E.
hasTrailType
Indicates that an entity (such as a trail or route) is associated with a specific type or category of trail.
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99a098e08190976eb4b019818f67 |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad9611fc348190a5d17d237f653f60 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:58 p.m.