Triple
T7444009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bône |
E171824
|
entity |
| Predicate | hasApproximatePopulationOfSuccessorCity |
P3412
|
FINISHED |
| Object | over 300000 inhabitants |
—
|
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: over 300000 inhabitants | Statement: [Bône, hasApproximatePopulationOfSuccessorCity, over 300000 inhabitants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximatePopulationOfSuccessorCity Context triple: [Bône, hasApproximatePopulationOfSuccessorCity, over 300000 inhabitants]
-
A.
hasPopulationApproximate
chosen
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
B.
hasPopulationOver
Indicates that one entity has a population greater than a specified number or than another entity.
-
C.
metropolitanAreaPopulationApproximate
Indicates that the predicate specifies an approximate total population size for a given metropolitan area.
-
D.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
E.
isThirdLargestCityIn
Indicates that a city is the third largest (typically by population or area) within a specified region or country.
- 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_69c68a65402881908f7869368eb746fb |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f36e9a588190b54b8bae181fc971 |
completed | March 27, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69c6f039f7248190bb4183f97b605763 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:13 p.m.