Triple
T32488831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Department |
E830321
|
entity |
| Predicate | populationRankInParaguay |
P188448
|
FINISHED |
| Object | most populous department |
—
|
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: most populous department | Statement: [Central Department, populationRankInParaguay, most populous department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInParaguay Context triple: [Central Department, populationRankInParaguay, most populous department]
-
A.
populationRankInBolivia
Indicates the relative position of an entity in terms of population size compared to other entities within Bolivia.
-
B.
countryCityParaguay
Indicates that a city is located within the country of Paraguay.
-
C.
populationRankInVenezuela
Indicates the relative position of an entity in terms of population size compared to other entities within Venezuela.
-
D.
populationRankInEcuador
Indicates the relative position of a place in terms of its population size compared to other places within Ecuador.
-
E.
hasPopulationRankInChile
Indicates the relative position of an entity in the ordered ranking of populations within Chile.
- F. None of above. chosen
Provenance (4 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_69f34920aa4081908d8fb0277414b911 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69fba789c1188190973a919bfe2871f3 |
completed | May 6, 2026, 8:41 p.m. |
Created at: May 1, 2026, 12:58 a.m.