Triple
T3480148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sami languages |
E73468
|
entity |
| Predicate | hasApproximateNumberOfVarieties |
P49018
|
FINISHED |
| Object | around 10 |
—
|
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: around 10 | Statement: [Sami languages, hasApproximateNumberOfVarieties, around 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfVarieties Context triple: [Sami languages, hasApproximateNumberOfVarieties, around 10]
-
A.
numberOfPrimaryVarieties
Indicates the count of distinct primary varieties associated with a given entity.
-
B.
has32Varieties
Indicates that one entity possesses or includes exactly 32 distinct types, forms, or varieties of another entity.
-
C.
colorVarietyCount
Indicates the number of distinct colors associated with or present in a given entity or set of entities.
-
D.
colorVarietyOf
Indicates that one entity represents a specific color variant or color option of another entity.
-
E.
hasApproximateVendorCount
Indicates that an entity is associated with an estimated or non-exact number of vendors.
- 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_69ad85b3c9b08190857cae74c7f36da9 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb7461708190898002fbd1191f34 |
completed | March 8, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69adae0935ac8190bfa8a8bd3dcd3301 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb1ecb02881908394f197e31431b4 |
completed | March 8, 2026, 5:29 p.m. |
Created at: March 8, 2026, 3:17 p.m.