Triple
T1187729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bantu languages |
E25285
|
entity |
| Predicate | estimatedNumberOfSpeakers |
P1247
|
FINISHED |
| Object | hundreds of millions |
—
|
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: hundreds of millions | Statement: [Bantu languages, estimatedNumberOfSpeakers, hundreds of millions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfSpeakers Context triple: [Bantu languages, estimatedNumberOfSpeakers, hundreds of millions]
-
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.
hasSpeakersIn
Indicates that an entity (such as an event, conference, or session) includes or is associated with speakers located in or belonging to a specified place or group.
-
C.
hasSpeakerType
Indicates that an entity functions in a particular role or category as a speaker (e.g., narrator, character, announcer) within a given context.
-
D.
estimatedNumberOfLanguages
Indicates the approximate count of distinct languages associated with an entity, typically based on estimation rather than an exact measurement.
-
E.
numberOfPersons
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd568cf481908d10cf19a3ce28f3 |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.