Triple
T17585523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 洙 |
E428310
|
entity |
| Predicate | belongsToRadical |
P128105
|
FINISHED |
| Object | radical 85 (water) |
—
|
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: radical 85 (water) | Statement: [洙, belongsToRadical, radical 85 (water)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToRadical Context triple: [洙, belongsToRadical, radical 85 (water)]
-
A.
semanticRadicalOfCharacter
Indicates that one element is the semantic radical (meaning-bearing component) of a given written character.
-
B.
kangxiRadicalName
Indicates the specific Kangxi radical name associated with a given Chinese character or radical index.
-
C.
isRadicalInHebrewDictionaryOrdering
Indicates that one term is ordered before another according to the radical-based sorting rules used in Hebrew dictionaries.
-
D.
radicalStrokeCount
Indicates the number of strokes used to write the radical component of a character.
-
E.
belongsToRomanizationFamily
Indicates that one romanization system is a member of, or classified under, a broader family or group of related romanization systems.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463d113b08190975506f3558c1eca |
completed | April 19, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb50b448190a59dd4be33c76db7 |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:50 a.m.