Triple
T700404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French |
E13984
|
entity |
| Predicate | nativeSpeakers |
P1246
|
FINISHED |
| Object | approximately 80 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: approximately 80 million | Statement: [French, nativeSpeakers, approximately 80 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nativeSpeakers Context triple: [French, nativeSpeakers, approximately 80 million]
-
A.
hasNativeSpeakers
Indicates that a language or dialect is spoken as a first language by one or more people or populations.
-
B.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
-
C.
countryWithSpeakers
Indicates that a given country is one in which speakers of a specified language (or languages) are present.
-
D.
hasApproximateNativeSpeakers
chosen
Indicates that an entity is associated with an estimated or approximate number of people who speak it as their native language.
-
E.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
- 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a544e3608190ac315c7aa9f88e7e |
completed | March 1, 2026, 8:44 p.m. |
| PD | Predicate disambiguation | batch_69a4a4ec8c748190b198492a0eea4445 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.