Triple
T37834125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klimov M-100 |
E943288
|
entity |
| Predicate | numberOfStrokes |
P148984
|
FINISHED |
| Object | four-stroke |
—
|
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: four-stroke | Statement: [Klimov M-100, numberOfStrokes, four-stroke]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStrokes Context triple: [Klimov M-100, numberOfStrokes, four-stroke]
-
A.
hasStrokeCount
Indicates the number of strokes required to write a given symbol or character.
-
B.
hasStrokeCountApprox
Indicates an approximate number of strokes associated with writing or drawing the related entity.
-
C.
numberOfStrokesPerCycle
chosen
Indicates the count of individual strokes that occur during one complete cycle of a repeated action or process.
-
D.
radicalStrokeCount
Indicates the number of strokes used to write the radical component of a character.
-
E.
hasStrokeOrder
Indicates that there is a specific, ordered sequence of strokes used to write or draw the related symbol or character.
- 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_69f76eea4c8c8190a335aed5955cf2db |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.