Triple
T5874365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flemish Dutch |
E130590
|
entity |
| Predicate | hasNormsFor |
P22982
|
FINISHED |
| Object | spelling |
—
|
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: spelling | Statement: [Flemish Dutch, hasNormsFor, spelling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNormsFor Context triple: [Flemish Dutch, hasNormsFor, spelling]
-
A.
hasNorm
chosen
Indicates that an entity is associated with, governed by, or characterized through a particular norm, rule, or standard.
-
B.
normativeFor
Indicates that something establishes, prescribes, or encodes the norms, standards, or rules that should govern another thing’s behavior or state.
-
C.
hasNormativeCategory
Indicates that something is associated with a particular normative category, such as a standard, rule, or evaluative classification that prescribes how it ought to be regarded or treated.
-
D.
hasHigherNorm
Indicates that one entity’s norm (such as magnitude, length, or size under a given norm) is greater than that of another entity.
-
E.
usesNormalization
Indicates that one entity applies or relies on a normalization process or technique in relation to another entity or data.
- 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_69c0085523688190bfd487479ce819e6 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0432fea5881909f5c291dd8db6105 |
completed | March 22, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69c033499ca08190bd26cee5b03f6306 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:57 p.m.