Triple
T8791064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sremska Mitrovica |
E209165
|
entity |
| Predicate | hasMunicipalPopulationApprox |
P38055
|
FINISHED |
| Object | 80000 |
—
|
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: 80000 | Statement: [Sremska Mitrovica, hasMunicipalPopulationApprox, 80000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalPopulationApprox Context triple: [Sremska Mitrovica, hasMunicipalPopulationApprox, 80000]
-
A.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
B.
municipalityPopulation
chosen
Indicates the total number of inhabitants living within a given municipality.
-
C.
metropolitanAreaPopulationApproximate
Indicates that the predicate specifies an approximate total population size for a given metropolitan area.
-
D.
hasUrbanAreaApprox
Indicates an approximate measure or estimate of the size or extent of an entity’s urban area.
-
E.
isMostPopulousMunicipalityOf
Indicates that a municipality has the largest population among all municipalities within the specified administrative area or region.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f8e6e4881909155c40c52bc082c |
completed | March 31, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1d48f08190b325a77d4c76d223 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:43 p.m.