Triple
T10293939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North American market |
E241433
|
entity |
| Predicate | requiresAdaptationOf |
P4577
|
FINISHED |
| Object | products to local regulations |
—
|
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: products to local regulations | Statement: [North American market, requiresAdaptationOf, products to local regulations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiresAdaptationOf Context triple: [North American market, requiresAdaptationOf, products to local regulations]
-
A.
isAdaptation
Indicates that one work is derived from, based on, or reinterprets the content of another work.
-
B.
hasWorkAdaptation
Indicates that an entity has a modified, adjusted, or alternative form specifically adapted for use in a work or professional context.
-
C.
adaptedTo
chosen
Indicates that one entity has been modified, adjusted, or evolved to function effectively within the conditions, requirements, or characteristics defined by another entity.
-
D.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
E.
usedInAdaptation
Indicates that something (such as a character, plot element, or work) is incorporated or appears within an adaptation of another original source.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d46fb08190b7694290692e47dc |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:42 a.m.