Triple
T21985026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hangul Syllables |
E542934
|
entity |
| Predicate | hasCanonicalDecomposition |
P146159
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hangul Syllables, hasCanonicalDecomposition, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCanonicalDecomposition Context triple: [Hangul Syllables, hasCanonicalDecomposition, yes]
-
A.
hasDecomposition
Indicates that something can be broken down or separated into constituent parts, components, or simpler elements.
-
B.
hasCanonicalRepresentation
Indicates that one entity is the standard or authoritative form in which another entity is represented.
-
C.
hasCanonicalBasis
Indicates that there exists a standard or preferred basis associated with an entity, typically used as the reference basis in its context.
-
D.
decomposesIn
Indicates that one entity breaks down or separates into another entity or set of entities as its components or products.
-
E.
hasCanonicalCharacter
Indicates that something is associated with or defined by its standard, officially recognized character representation.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12708cdcc81909511d9f81bd8f20e |
completed | April 28, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
| PDg | Predicate description generation | batch_69e6fad4a540819096cdd5ea08527220 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:04 p.m.