Triple
T4335799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sa'idi Arabic |
E97458
|
entity |
| Predicate | hasSpeakerPopulationEstimate |
P36744
|
FINISHED |
| Object | tens 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: tens of millions | Statement: [Sa'idi Arabic, hasSpeakerPopulationEstimate, tens of millions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeakerPopulationEstimate Context triple: [Sa'idi Arabic, hasSpeakerPopulationEstimate, tens of millions]
-
A.
haveSpeakerPopulation
chosen
Indicates that an entity has a specified number or population size of people who speak a particular language.
-
B.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
C.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
D.
hasPopulationOver
Indicates that one entity has a population greater than a specified number or than another entity.
-
E.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given 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_69b3454662a481908fbcd0bbfaa3a0a4 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35152bfc88190ab5d53ca38f98d8a |
completed | March 12, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69b34f4e13fc8190a42c519f37959d27 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:14 p.m.