Triple
T636398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swedish language |
E16630
|
entity |
| Predicate | hasNumberOfSpeakersEstimate |
P1247
|
FINISHED |
| Object | about 10 million |
—
|
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: about 10 million | Statement: [Swedish language, hasNumberOfSpeakersEstimate, about 10 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSpeakersEstimate Context triple: [Swedish language, hasNumberOfSpeakersEstimate, about 10 million]
-
A.
hasApproximateTotalSpeakers
chosen
Indicates that an entity is associated with an estimated or roughly calculated number of total speakers, rather than an exact count.
-
B.
hasApproximateNativeSpeakers
Indicates that an entity is associated with an estimated or approximate number of people who speak it as their native language.
-
C.
hasApproximateNumberOfLanguages
Indicates that an entity is associated with a quantity representing an estimated or non-exact count of languages.
-
D.
hasNativeSpeakers
Indicates that a language or dialect is spoken as a first language by one or more people or populations.
-
E.
estimatedNumberOfLanguages
Indicates the approximate count of distinct languages associated with an entity, typically based on estimation rather than an exact measurement.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee7fdbc8190858e42bb1bfdb3ff |
completed | March 1, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69a49d0483908190a5ec42a7403c258e |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.