Triple
T23363696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Zucchelli Station |
E593252
|
entity |
| Predicate | typicalSummerPopulation |
P8162
|
FINISHED |
| Object | approximately 40 |
—
|
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: approximately 40 | Statement: [Mario Zucchelli Station, typicalSummerPopulation, approximately 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSummerPopulation Context triple: [Mario Zucchelli Station, typicalSummerPopulation, approximately 40]
-
A.
seasonalPopulation
chosen
Indicates a relationship where the number of individuals in a population varies depending on the season or time of year.
-
B.
staffPopulationApprox
Indicates an approximate or estimated number of staff associated with an entity.
-
C.
typicalCatchmentPopulation
Indicates the usual or expected number of people served by, or falling within the service area of, a given facility or resource.
-
D.
winterPopulationApprox
Indicates an approximate count or estimate of a population present during the winter season.
-
E.
permanentPopulation
Indicates that an entity has a stable, long-term resident population rather than a temporary or transient presence.
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0aac4248190a4663ed12aed6856 |
completed | April 29, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:31 p.m.